A patent technology opportunity identification method, system, device and medium

Abstract

The patent application provides a patent technology opportunity identification method, system, device and medium, comprising: extracting opportunity identification basic data of a target technical field from a patent database, a non-patent literature database and a product market database respectively; based on the opportunity identification basic data, constructing a patent technology and efficacy matrix, a non-patent literature technology and problem matrix and a product technology and bottleneck matrix respectively; using a patent technology opportunity identification algorithm, patent technology opportunity identification is performed on the patent technology and efficacy matrix, the non-patent literature technology and problem matrix and the product technology and bottleneck matrix to generate a patent technology opportunity list; by extracting basic data from patents, non-patent literature and product markets, and constructing technology-efficacy, technology-problem and technology-bottleneck matrices, using a patent technology opportunity identification algorithm, the defects of relying on a single data source, strong subjectivity and difficulty in discovering potential high-value opportunities in the prior art are systematically overcome.

Description

Technical Field

[0001] This patent application relates to the field of text processing technology, specifically to a patented technology opportunity identification method, system, device, and medium. Background Technology

[0002] In today's highly competitive technological environment, the ability of enterprises and innovation entities to quickly and accurately identify potential technological opportunities and effectively deploy patents has become crucial for gaining and maintaining a competitive advantage. Traditional methods for identifying patent opportunities mainly rely on analyzing patent databases, such as mining technical themes in patent texts, analyzing technology efficacy matrices, or tracking technology lifecycles to predict development trends.

[0003] However, this type of method has obvious limitations: First, its analysis dimension is too singular, focusing excessively on the published patent documents themselves, resulting in the identification results lagging behind the latest technological breakthroughs; second, this method also fails to effectively incorporate product market data that reflects market demand and productization bottlenecks, causing the identified technological opportunities to lack commercial applicability and market relevance, and to fail to match real industry pain points.

[0004] In recent years, with the development of artificial intelligence technology, some solutions have emerged that use machine learning models to automatically analyze massive amounts of data to discover technological opportunities. However, these solutions typically operate as a "black box," with opaque internal logic, poor interpretability, and heavy reliance on large amounts of high-quality training data, making their reliability difficult to assess. This makes it hard for patent analysts and decision-makers to understand and trust their output. Furthermore, existing methods often lack a systematic and structured analytical framework, relying too heavily on the analyst's personal experience and intuitive judgment, making it difficult to comprehensively and objectively uncover cross-domain, disruptive technological opportunities, potentially missing crucial patent deployment windows. Summary of the Invention

[0005] To overcome the shortcomings of the prior art, this patent application proposes a method for identifying patent opportunities, comprising: Basic data for opportunity identification in the target technology field were extracted from patent databases, non-patent literature databases, and product market databases, respectively. Based on the aforementioned opportunity identification data, a patent technology and efficacy matrix, a non-patent literature technology and problem matrix, and a product technology and bottleneck matrix are constructed respectively. A patent technology opportunity identification algorithm is used to identify patent technology opportunities in the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix, and generate a list of patent technology opportunities.

[0006] Preferably, the extraction of opportunity identification basic data from patent databases, non-patent literature databases, and product market databases respectively includes: Retrieve patent texts in the target technical field from the patent database, and extract the classification number, invention title, specification, and claims of the patent texts; In non-patent literature databases, retrieve articles corresponding to the patent text, and extract the abstract, keywords, main text, introduction, and conclusion of the articles; In the product market database, retrieve the product market data corresponding to the patent text, and extract the technical summary, technical route, iteration plan, manufacturer's self-description, and market feedback of the product market data; The classification number, invention title, specification, claims, abstract, keywords, main text, introduction, conclusion, technical overview, technical route, iteration plan, manufacturer's statement, and market feedback are cleaned and standardized to serve as the basis for opportunity identification.

[0007] Preferably, after extracting opportunity identification basic data of the target technology field from the patent database, non-patent literature database, and product market database respectively, and before constructing the patent technology and efficacy matrix, non-patent literature technology and problem matrix, and product technology and bottleneck matrix based on the opportunity identification basic data, the method further includes: Using the main classification number of the patent text as the technical classification identifier, patent texts with the same classification number or patent texts with the same first four classification numbers are classified into the same technical subfield. Based on the keywords of the articles, each article is divided into a corresponding technical subfield; Based on the technical overview of the product market data, each product is categorized into its corresponding technical subfield.

[0008] Preferably, the construction of a patent technology and efficacy matrix, a non-patent literature technology and problem matrix, and a product technology and bottleneck matrix based on the opportunity identification data includes: From the opportunity identification basic data corresponding to the patent text, technical means features and corresponding functional efficacy information features are extracted to construct a patent technology and efficacy matrix. From the opportunity identification basic data corresponding to the articles, we extract the features of cutting-edge technology points and scientific questions to construct a non-patent literature technology and question matrix. From the opportunity identification base data corresponding to the product market data, extract the technical element characteristics and application problem characteristics of commercial products, and construct a product technology and bottleneck matrix.

[0009] Preferably, the step of extracting technical means features and corresponding functional efficacy information features from the opportunity identification basic data corresponding to the patent text, and constructing a patent technology and efficacy matrix, includes: Set up a first two-dimensional matrix with technical means features as rows and functional and efficacy information features as columns; From the claims of the opportunity identification basic data corresponding to the patent text, extract the core technical features and specific structures, components, materials, and process steps of the patent text as technical means features; Information describing the technical effects is extracted from the specification of the opportunity identification basic data corresponding to the patent text and used as functional efficacy information features. The extracted technical features and functional efficacy information features are filled into the first two-dimensional matrix to construct the patent technology and efficacy matrix.

[0010] Preferably, the step of extracting cutting-edge technology features and scientific question features from the opportunity identification basic data corresponding to the article, and constructing a non-patent literature technology and question matrix, includes: Set up a second two-dimensional matrix with features of cutting-edge technologies as rows and features of scientific questions as columns; From the summary, keywords, and main text of the opportunity identification basic data corresponding to the article, extract the novel methods, new materials, unique structures, improved algorithms, or innovative experimental schemes of the article as features of cutting-edge technologies; Extract the core scientific challenges or technical bottlenecks of the article from the abstract, introduction, and conclusion of the opportunity identification basic data corresponding to the article, and use them as the features of the scientific problem. The extracted cutting-edge technology features and scientific problem features are filled into the second two-dimensional matrix to construct a non-patent literature technology and problem matrix.

[0011] Preferably, the step of extracting commercial product technology element features and application problem features from the opportunity identification basic data corresponding to the product market data, and constructing a product technology and bottleneck matrix, includes: Set up a third two-dimensional matrix with the technical features of commercial products as rows and the application problems of products as columns; From the technical overview, technical roadmap, and iteration plan of the opportunity identification basic data corresponding to the product market data, mature technical solutions of the product market data are extracted as technical element features of commercial products. The application problem characteristics of the product are extracted from the manufacturer's self-report, iteration plan and market feedback from the opportunity identification basic data corresponding to the product market data; The extracted commercial product technology elements and product application problems are filled into the third two-dimensional matrix to construct the product technology and bottleneck matrix.

[0012] Preferably, the patent technology opportunity identification algorithm is used to identify patent technology opportunities in the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix, generating a patent technology opportunity list, including: Obtain a matrix of patent technologies and their effectiveness, a matrix of non-patent literature technologies and their problems, and a matrix of product technologies and their bottlenecks within the same technology subfield; A blank opportunity identification algorithm is used to calculate blank opportunity scores for the patent technology and efficacy matrix, non-patent literature technology and problem matrix, and product technology and bottleneck matrix in the same technology subfield, and to identify blank patent technology opportunities based on the blank opportunity scores. An alternative opportunity identification algorithm is used to identify existing solutions and alternative paths for each problem in the patent technology and efficacy matrix, non-patent literature technology and problem matrix, and product technology and bottleneck matrix of the same technology subfield, and to identify alternative patent technology opportunities based on the existing solutions and alternative paths. An evolutionary opportunity identification algorithm is used to calculate the evolutionary opportunity scores of the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix in the same technology subfield. Based on the evolutionary opportunity scores, evolutionary patent technology opportunities are identified. A list of patent opportunities is generated based on the blank patent opportunities, the alternative patent opportunities, and the evolutionary patent opportunities.

[0013] Preferably, the blank opportunity identification algorithm is used to calculate blank opportunity scores for the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix in the same technology subfield. Based on the blank opportunity scores, blank patent technology opportunities are identified, including: A three-dimensional feature space of technology-efficacy-problem is constructed with technical parameters, efficacy parameters, and problem parameters as axes; the three-dimensional feature space of technology-efficacy-problem includes multiple technical units; The technical means characteristics and functional efficacy information characteristics of each pair in the patent technology and efficacy matrix of the same technical subfield, the cutting-edge technical point characteristics and scientific problem characteristics of each pair in the non-patent literature technology and problem matrix, and the commercial product technology element characteristics and application problem characteristics of each pair in the product technology and bottleneck matrix are respectively mapped into the three-dimensional feature space of technology-efficacy-problem. After scanning and determining the patent data points, literature data points, and product data points of each technical unit in the three-dimensional feature space of technology-efficacy-problem, the patent gap degree, literature problem concentration degree, and product bottleneck intensity are determined based on the patent data points, literature data points, and product data points. Based on the patent vacancy rate, the concentration of literature issues, and the product bottleneck intensity and their corresponding weights, a blank opportunity score is calculated for each technology unit. When the blank opportunity score exceeds a preset threshold and the technical feasibility assessment meets the standard, the content of the corresponding technology unit is marked as a blank patent technology opportunity. The technical unit consists of a unique technology, efficacy, and problem.

[0014] Preferably, the blank opportunity score is calculated as follows:

[0015] in, Rate the blank opportunity. For patent gaps, As a weight for patent vacancy, For the concentration of literature questions, The weight of the concentration of literature questions, For product bottleneck strength, The weighting of the bottleneck strength of the product.

[0016] Preferably, the alternative opportunity identification algorithm is used to identify existing solutions and alternative paths for each problem in the patent technology and efficacy matrix, non-patent literature technology and problem matrix, and product technology and bottleneck matrix within the same technology subfield. Based on the existing solutions and alternative paths, alternative patent technology opportunities are identified, including: From the patent technology and efficacy matrix of the same technology subfield, technical means that match the application problems in the product technology and bottleneck matrix are retrieved to generate a set of existing technical solutions; the set of existing technical solutions includes multiple existing technical solutions. In the non-patent literature technology and problem matrix, cutting-edge technology points that can solve the application problem are retrieved to generate a set of candidate alternative paths; the set of candidate alternative paths includes multiple candidate alternative path schemes. Analyze the technical path differences between existing technical solutions and corresponding candidate alternative solutions, and calculate the substitution potential index of candidate alternative solutions; When the substitution potential index is greater than the industry benchmark and there is technological substitution feasibility, the corresponding candidate substitution path scheme is marked as a substitute patent technology opportunity.

[0017] Preferably, the step of employing an evolutionary opportunity identification algorithm to calculate the evolutionary opportunity scores of the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix within the same technology subfield, and identifying evolutionary patent technology opportunities based on the evolutionary opportunity scores, includes: Extract the next-generation technology direction from the iterative plan of the product technology and bottleneck matrix in the same technology subfield; The next-generation technology direction is cross-validated and reverse-mapped with the cutting-edge technology points of the non-patent literature technology and problem matrix to generate multiple iterative technologies; For each iterative technology, a technological evolution projection is performed. During the projection process, the technological growth rate, efficiency leap probability, and market demand matching degree of each iterative technology are extracted, and a technological evolution opportunity score for each iterative technology is calculated. Based on the aforementioned technology evolution opportunity score, iterative technologies that are in the technology growth stage and have the characteristics of efficiency leaps are identified and marked as evolutionary patent technology opportunities.

[0018] Based on the same inventive concept, this patent application also provides a patent technology opportunity identification system, including: an opportunity identification basic data extraction module, a matrix construction module, and a patent technology opportunity list generation module; The opportunity identification basic data extraction module is used to extract opportunity identification basic data in the target technology field from the patent database, non-patent literature database and product market database respectively. The matrix construction module is used to construct, based on the opportunity identification basic data, a patent technology and efficacy matrix, a non-patent literature technology and problem matrix, and a product technology and bottleneck matrix, respectively. The patent technology opportunity list generation module is used to identify patent technology opportunities in the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix by using a patent technology opportunity identification algorithm, and generate a patent technology opportunity list.

[0019] Preferably, the opportunity identification basic data extraction module is specifically used for: Retrieve patent texts in the target technical field from the patent database, and extract the classification number, invention title, specification, and claims of the patent texts; In non-patent literature databases, retrieve articles corresponding to the patent text, and extract the abstract, keywords, main text, introduction, and conclusion of the articles; In the product market database, retrieve the product market data corresponding to the patent text, and extract the technical summary, technical route, iteration plan, manufacturer's self-description, and market feedback of the product market data; The classification number, invention title, specification, claims, abstract, keywords, main text, introduction, conclusion, technical overview, technical route, iteration plan, manufacturer's statement, and market feedback are cleaned and standardized to serve as the basis for opportunity identification.

[0020] Preferably, the system further includes: a patent article product corresponding module; the patent article product corresponding module is used for: Using the main classification number of the patent text as the technical classification identifier, patent texts with the same classification number or patent texts with the same first four classification numbers are classified into the same technical subfield. Based on the keywords of the articles, each article is divided into a corresponding technical subfield; Based on the technical overview of the product market data, each product is categorized into its corresponding technical subfield.

[0021] Preferably, the matrix construction module includes: The patent technology and efficacy matrix construction submodule is used to extract technical means features and corresponding functional efficacy information features from the opportunity identification basic data corresponding to the patent text, and construct the patent technology and efficacy matrix. The non-patent literature technology and problem matrix construction submodule is used to extract cutting-edge technology features and scientific problem features from the opportunity identification basic data corresponding to the articles, and construct the non-patent literature technology and problem matrix. The product technology and bottleneck matrix construction submodule is used to extract the characteristics of commercial product technology elements and application problem characteristics from the opportunity identification basic data corresponding to the product market data, and construct the product technology and bottleneck matrix.

[0022] Preferably, the patent technology and efficacy matrix construction submodule is specifically used for: Set up a first two-dimensional matrix with technical means features as rows and functional and efficacy information features as columns; From the claims of the opportunity identification basic data corresponding to the patent text, extract the core technical features and specific structures, components, materials, and process steps of the patent text as technical means features; Information describing the technical effects is extracted from the specification of the opportunity identification basic data corresponding to the patent text and used as functional efficacy information features. The extracted technical features and functional efficacy information features are filled into the first two-dimensional matrix to construct the patent technology and efficacy matrix.

[0023] Preferably, the non-patent literature technology and problem matrix construction submodule is specifically used for: Set up a second two-dimensional matrix with features of cutting-edge technologies as rows and features of scientific questions as columns; From the summary, keywords, and main text of the opportunity identification basic data corresponding to the article, extract the novel methods, new materials, unique structures, improved algorithms, or innovative experimental schemes of the article as features of cutting-edge technologies; Extract the core scientific challenges or technical bottlenecks of the article from the abstract, introduction, and conclusion of the opportunity identification basic data corresponding to the article, and use them as the features of the scientific problem. The extracted cutting-edge technology features and scientific problem features are filled into the second two-dimensional matrix to construct a non-patent literature technology and problem matrix.

[0024] Preferably, the product technology and bottleneck matrix construction submodule is specifically used for: Set up a third two-dimensional matrix with the technical features of commercial products as rows and the application problems of products as columns; From the technical overview, technical roadmap, and iteration plan of the opportunity identification basic data corresponding to the product market data, mature technical solutions of the product market data are extracted as technical element features of commercial products. The application problem characteristics of the product are extracted from the manufacturer's self-report, iteration plan and market feedback from the opportunity identification basic data corresponding to the product market data; The extracted commercial product technology elements and product application problems are filled into the third two-dimensional matrix to construct the product technology and bottleneck matrix.

[0025] Preferably, the patent opportunity list generation module includes: The patent article product extraction submodule is used to obtain the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix in the same technology subfield. The blank patent technology opportunity identification submodule is used to calculate the blank opportunity score of the patent technology and efficacy matrix, non-patent literature technology and problem matrix and product technology and bottleneck matrix in the same technology subfield using the blank opportunity identification algorithm, and to identify blank patent technology opportunities based on the blank opportunity score. The alternative patent technology opportunity identification submodule is used to identify existing solutions and alternative paths for each problem in the patent technology and efficacy matrix, non-patent literature technology and problem matrix, and product technology and bottleneck matrix of the same technology subfield using an alternative opportunity identification algorithm, and to identify alternative patent technology opportunities based on the existing solutions and alternative paths. The evolutionary patent technology opportunity identification submodule is used to calculate the evolutionary opportunity score of the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix in the same technology subfield using the evolutionary opportunity identification algorithm, and to identify evolutionary patent technology opportunities based on the evolutionary opportunity score. The patent technology opportunity list generation submodule is used to generate a patent technology opportunity list based on the blank patent technology opportunities, the alternative patent technology opportunities, and the evolutionary patent technology opportunities.

[0026] Preferably, the blank patent technology opportunity identification submodule is specifically used for: A three-dimensional feature space of technology-efficacy-problem is constructed with technical parameters, efficacy parameters, and problem parameters as axes; the three-dimensional feature space of technology-efficacy-problem includes multiple technical units; The technical means characteristics and functional efficacy information characteristics of each pair in the patent technology and efficacy matrix of the same technical subfield, the cutting-edge technical point characteristics and scientific problem characteristics of each pair in the non-patent literature technology and problem matrix, and the commercial product technology element characteristics and application problem characteristics of each pair in the product technology and bottleneck matrix are respectively mapped into the three-dimensional feature space of technology-efficacy-problem. After scanning and determining the patent data points, literature data points, and product data points of each technical unit in the three-dimensional feature space of technology-efficacy-problem, the patent gap degree, literature problem concentration degree, and product bottleneck intensity are determined based on the patent data points, literature data points, and product data points. Based on the patent vacancy rate, the concentration of literature issues, and the product bottleneck intensity and their corresponding weights, a blank opportunity score is calculated for each technology unit. When the blank opportunity score exceeds a preset threshold and the technical feasibility assessment meets the standard, the content of the corresponding technology unit is marked as a blank patent technology opportunity. The technical unit consists of a unique technology, efficacy, and problem.

[0027] Preferably, the blank opportunity score is calculated as follows:

[0028] in, Rate the blank opportunity. For patent gaps, As a weight for patent vacancy, For the concentration of literature questions, The weight of the concentration of literature questions, For product bottleneck strength, The weighting of the bottleneck strength of the product.

[0029] Preferably, the alternative patent technology opportunity identification submodule is specifically used for: From the patent technology and efficacy matrix of the same technology subfield, technical means that match the application problems in the product technology and bottleneck matrix are retrieved to generate a set of existing technical solutions; the set of existing technical solutions includes multiple existing technical solutions. In the non-patent literature technology and problem matrix, cutting-edge technology points that can solve the application problem are retrieved to generate a set of candidate alternative paths; the set of candidate alternative paths includes multiple candidate alternative path schemes. Analyze the technical path differences between existing technical solutions and corresponding candidate alternative solutions, and calculate the substitution potential index of candidate alternative solutions; When the substitution potential index is greater than the industry benchmark and there is technological substitution feasibility, the corresponding candidate substitution path scheme is marked as a substitute patent technology opportunity.

[0030] Preferably, the evolutionary patent technology opportunity recognition submodule is specifically used for: Extract the next-generation technology direction from the iterative plan of the product technology and bottleneck matrix in the same technology subfield; The next-generation technology direction is cross-validated and reverse-mapped with the cutting-edge technology points of the non-patent literature technology and problem matrix to generate multiple iterative technologies; For each iterative technology, a technological evolution projection is performed. During the projection process, the technological growth rate, efficiency leap probability, and market demand matching degree of each iterative technology are extracted, and a technological evolution opportunity score for each iterative technology is calculated. Based on the aforementioned technology evolution opportunity score, iterative technologies that are in the technology growth stage and have the characteristics of efficiency leaps are identified and marked as evolutionary patent technology opportunities.

[0031] Based on the same inventive concept, this patent application also provides an electronic device, comprising: at least one processor and a memory; wherein the memory and the processor are connected via a bus. The memory is used to store one or more programs; When the one or more programs are executed by the at least one processor, a patent technology opportunity identification method as described above is implemented.

[0032] Based on the same inventive concept, this patent application also provides a readable storage medium having a computer program stored thereon and an executable program stored thereon, wherein when the executable program is executed, it implements the patented technology opportunity identification method as described above.

[0033] Compared with the closest prior art, the beneficial effects of this invention patent application are as follows: This invention patent application provides a method, system, device, and medium for identifying patent technology opportunities, comprising: extracting basic data for opportunity identification in a target technology field from a patent database, a non-patent literature database, and a product market database, respectively; constructing a patent technology and efficacy matrix, a non-patent literature technology and problem matrix, and a product technology and bottleneck matrix based on the basic data for opportunity identification; and using a patent technology opportunity identification algorithm to identify patent technology opportunities in the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix, thereby generating a list of patent technology opportunities. This invention extracts basic data from three distinct but interconnected data sources—patents, non-patent literature, and product markets—and constructs a structured patent technology and efficacy matrix, a non-patent literature technology and problem matrix, and a product market matrix, respectively. The patent literature technology and problem matrix and product technology and bottleneck matrix are ultimately fused and analyzed using a specialized patent technology opportunity identification algorithm. This systematically overcomes the shortcomings of existing technologies, such as reliance on a single data source, strong subjectivity, and difficulty in discovering potential high-value opportunities. This method effectively correlates and connects scattered technical information, research hotspots, and market pain points. It can not only identify the technological gaps in the current patent layout, but also accurately locate emerging technology paths with substitution potential, cross-domain technology integration opportunities, and forward-looking layout directions that conform to the trend of technological evolution. Thus, it provides enterprises and R&D institutions with a data-driven, logically clear, and prioritized list of patent technology opportunities, significantly improving the strategic, accurate, and forward-looking nature of patent layout, and effectively reducing the blindness of R&D innovation and patent risks. Attached Figure Description

[0034] Figure 1 A schematic flowchart of a patent opportunity identification method provided for this invention patent application; Figure 2 A schematic diagram of the technical subfield provided for this invention patent application is generated. Figure 3 The schematic diagram of the generation of the three matrices provided in this patent application; Figure 4 A schematic diagram illustrating the generation of a list of patent technology opportunities for this invention's patent application; Figure 5 A schematic diagram of a patent technology opportunity identification system provided for this invention patent application; Figure 6 This is a schematic diagram of the structure of an electronic device provided in this patent application. Detailed Implementation

[0035] The specific embodiments of this patent application will be further described in detail below with reference to the accompanying drawings.

[0036] Example 1: This invention patent application provides a patent technology opportunity identification method, such as... Figure 1 As shown, it includes: Step 1: Extract basic data for opportunity identification in the target technology field from patent databases, non-patent literature databases, and product market databases, respectively; Step 2: Based on the opportunity identification data, construct the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix, respectively; Step 3: Using a patent technology opportunity identification algorithm, identify patent technology opportunities in the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix to generate a list of patent technology opportunities.

[0037] In one implementation, such as Figure 2 As shown in step 1 above, extracting opportunity identification basic data from patent databases, non-patent literature databases, and product market databases respectively includes: Retrieve patent texts in the target technical field from the patent database, and extract the classification number, invention title, specification, and claims of the patent texts; In non-patent literature databases, retrieve articles corresponding to the patent text, and extract the abstract, keywords, main text, introduction, and conclusion of the articles; In the product market database, retrieve the product market data corresponding to the patent text, and extract the technical summary, technical route, iteration plan, manufacturer's self-description, and market feedback of the product market data; The classification number, invention title, specification, claims, abstract, keywords, main text, introduction, conclusion, technical summary, technical route, iteration plan, manufacturer's description, and market feedback are cleaned and standardized as basic data for opportunity identification. This invention constructs a systematic collection and preprocessing process for multi-source heterogeneous data. First, it accurately extracts core legal texts, including classification number, invention title, specification, and claims, from patent databases to ensure the complete capture of the legal protection scope and innovative points of the technical solution. Simultaneously, it obtains abstracts, keywords, main text, introductions, and conclusions of academic articles on corresponding technical topics from non-patent literature databases to deeply reveal the technical... The data collection process involves: understanding the principles of the technology, identifying unresolved issues, and exploring cutting-edge research trends; further, gathering technical descriptions, technical routes, iteration plans, manufacturer accounts, and market feedback from product market databases to directly reflect the current state of technology implementation, industry planning, and market demand pain points; and effectively resolving the information fragmentation and semantic ambiguity issues caused by dispersed data sources and inconsistent structures in traditional methods through unified data cleaning (noise removal and error correction) and data standardization (unified terminology and standardized formats). This provides a high-quality, multi-dimensional, and computable foundational data carrier for subsequent technology opportunity identification algorithms, fundamentally improving the accuracy, comprehensiveness, and industry relevance of patent technology opportunity discovery, and overcoming the inherent defects of single patent analysis being divorced from market and research realities.

[0038] In one implementation, after extracting opportunity identification basic data of the target technology field from the patent database, non-patent literature database, and product market database respectively, and before constructing the patent technology and efficacy matrix, non-patent literature technology and problem matrix, and product technology and bottleneck matrix based on the opportunity identification basic data, the method further includes: Using the main classification number of the patent text as the technical classification identifier, patent texts with the same classification number or patent texts with the same first four classification numbers are classified into the same technical subfield. Based on the keywords of the articles, each article is divided into a corresponding technical subfield; Based on the technical descriptions of the product market data, each product is categorized into its corresponding technical subfield. Before constructing the analysis matrix after completing multi-source data collection, this invention introduces a unified technical subfield classification mechanism based on the International Classification of Patents (ICP-ICP). This mechanism uses the main classification number or the first four identical high-order classification numbers of the patent text as authoritative technical classification identifiers, accurately classifying patent data into their corresponding technical subfields. Then, using this classification system as a unified coordinate, non-patent documents are intelligently classified into the same technical subfield based on semantic matching of article keywords. Market data is simultaneously categorized into the corresponding field based on the content characteristics of the product technical descriptions. This standardized method effectively solves the data fragmentation problem caused by heterogeneous classification systems in traditional multi-source data analysis. It ensures that patent, literature, and product data are constructed and analyzed within a unified technical boundary, thereby fundamentally eliminating semantic ambiguity and domain bias in cross-data source comparisons. This lays a solid data foundation for accurately identifying technological gaps, integration opportunities, and evolutionary paths, significantly improving the accuracy of technological opportunity discovery and its industry guidance value.

[0039] In one implementation, such as Figure 3 As shown in step 2 above, based on the opportunity identification data, the construction of the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix includes: From the opportunity identification basic data corresponding to the patent text, technical means features and corresponding functional efficacy information features are extracted to construct a patent technology and efficacy matrix. From the opportunity identification basic data corresponding to the articles, we extract the features of cutting-edge technology points and scientific questions to construct a non-patent literature technology and question matrix. From the opportunity identification base data corresponding to the product market data, the technical element characteristics and application problem characteristics of commercial products are extracted to construct a product technology and bottleneck matrix. This invention constructs a three-in-one matrix analysis system by structurally analyzing the technical and problem dimensions of multi-source data: First, the technical means characteristics and their functional efficacy information recorded in the claims and specifications are accurately extracted from the patent text to form a patent technology and efficacy matrix with technical means as rows and functional efficacy as columns, intuitively showing the distribution of legally protected technical solutions; at the same time, the characteristics of cutting-edge technical points and the scientific problems they aim to solve are mined from non-patent literature to construct a non-patent literature technology and problem matrix, revealing the core scientific problems that have not yet been solved at the forefront of scientific research; further, the technical element characteristics of commercial products and their application problem characteristics exposed in actual applications are extracted from the product market data to form a product technology and bottleneck matrix, which truly reflects the technical pain points in the industrialization process. This construction method transforms legal texts, scientific research literature, and market feedback into a matrix expression of "technology-attributes," which not only achieves homogenization of multi-source heterogeneous data but also establishes a calculable correlation between the scope of patent protection, research directions, and market demand pain points. This provides a structured data foundation for accurately identifying technological gaps, alternative paths, and evolutionary directions through matrix operations, completely changing the predicament of traditional technology opportunity analysis that relies on qualitative descriptions and lacks quantitative evidence.

[0040] In one implementation, the step of extracting technical means features and corresponding functional efficacy information features from the opportunity identification basic data corresponding to the patent text, and constructing a patent technology and efficacy matrix, includes: Set up a first two-dimensional matrix with technical means features as rows and functional and efficacy information features as columns; From the claims of the opportunity identification basic data corresponding to the patent text, extract the core technical features and specific structures, components, materials, and process steps of the patent text as technical means features; Information describing the technical effects is extracted from the specification of the opportunity identification basic data corresponding to the patent text and used as functional efficacy information features. The extracted technical means features and functional efficacy information features are filled into the first two-dimensional matrix to construct a patent technology and efficacy matrix. This invention achieves standardized analysis and structured representation of patent technical solutions by constructing a first two-dimensional matrix with technical means features as rows and functional efficacy information features as columns. Specifically, it accurately extracts technical means features that embody the core technological contribution of the invention from the patent claims, including substantive technical elements such as specific structures, components, materials, and process steps, ensuring that the extracted features directly correspond to the scope of legal protection. Simultaneously, it systematically extracts functional efficacy information features that clearly describe the technical effects from the specification, fully reflecting the performance achieved by the technical solution. Improvements and functional enhancements: By establishing a correspondence between the extracted technical means features and functional efficacy information features and filling them into a preset matrix framework, the constructed patent technology and efficacy matrix not only clearly presents the mapping relationship between each technical solution and its achieved efficacy in a specific technical field, but also transforms the complex technical information that originally existed in natural language descriptions into a standardized data model that is machine-readable and computable. This provides an accurate data foundation for subsequent identification of technical gaps and assessment of technical layout density through matrix operations, effectively overcoming the shortcomings of traditional patent analysis, which relies on manual interpretation and is characterized by strong subjectivity, low efficiency, and difficulty in quantitative comparison. This significantly improves the objectivity and systematicness of patent technology opportunity identification.

[0041] In one implementation, the step of extracting cutting-edge technology features and scientific question features from the opportunity identification basic data corresponding to the article, and constructing a non-patent literature technology and question matrix, includes: Set up a second two-dimensional matrix with features of cutting-edge technologies as rows and features of scientific questions as columns; From the summary, keywords, and main text of the opportunity identification basic data corresponding to the article, extract the novel methods, new materials, unique structures, improved algorithms, or innovative experimental schemes of the article as features of cutting-edge technologies; Extract the core scientific challenges or technical bottlenecks of the article from the abstract, introduction, and conclusion of the opportunity identification basic data corresponding to the article, and use them as the features of the scientific problem. The extracted cutting-edge technology features and scientific problem features are filled into the second two-dimensional matrix to construct a non-patent literature technology and problem matrix. This invention establishes a systematic mapping system for cutting-edge scientific technologies by constructing a second two-dimensional matrix with cutting-edge technology features as rows and scientific problem features as columns. Specifically, it accurately extracts novel methods, new materials, unique structures, improved algorithms, or innovative experimental schemes that embody academic innovation from the abstracts, keywords, and main text of non-patent literature as cutting-edge technology features, ensuring complete coverage of the latest scientific research progress. Simultaneously, it deeply mines the core scientific problems and technological bottlenecks that the literature aims to solve from the abstracts, introductions, and conclusions as scientific problem features, accurately reflecting… Key issues that have not yet been addressed in the field; by establishing a correspondence between the extracted cutting-edge technology features and scientific problem features and filling them into a preset matrix framework, the constructed non-patent literature technology and problem matrix not only clearly presents the network of connections between scientific research innovation directions and problems to be solved in specific technical fields, but also transforms unstructured academic texts into standardized data structures that can be quantified and analyzed. This provides reliable scientific research dimension input for subsequent identification of technical research hotspots and gaps and prediction of technology integration trends. It effectively solves the pain points of traditional academic analysis, which relies on expert experience, resulting in limited scope, low efficiency, and difficulty in co-analyzing with patent and market data, and significantly improves the foresight and scientific nature of technology opportunity identification.

[0042] In one implementation, the step of extracting commercial product technology element features and application problem features from the opportunity identification basic data corresponding to the product market data, and constructing a product technology and bottleneck matrix, includes: Set up a third two-dimensional matrix with the technical features of commercial products as rows and the application problems of products as columns; From the technical overview, technical roadmap, and iteration plan of the opportunity identification basic data corresponding to the product market data, mature technical solutions of the product market data are extracted as technical element features of commercial products. The application problem characteristics of the product are extracted from the manufacturer's self-report, iteration plan and market feedback from the opportunity identification basic data corresponding to the product market data; The extracted commercial product technology elements and application problems are filled into the third two-dimensional matrix to construct a product technology and bottleneck matrix. This invention establishes a precise mapping system between the current state of industrial technology and market demand pain points by constructing a third two-dimensional matrix with commercial product technology element characteristics as rows and application problem characteristics as columns. Specifically, it systematically extracts mature, market-proven technical solutions from the product market data's technical descriptions, technical routes, and iteration plans as commercial product technology element characteristics, ensuring that the selected characteristics represent technical entities with commercial feasibility. Simultaneously, it deeply mines the performance defects, user experience pain points, and technical bottlenecks exposed by the product in actual application scenarios from manufacturer self-reports, iteration plans, and market feedback. Limitations, as characteristics of application problems, truly reflect the urgent needs and technological bottlenecks of the end market. By establishing a correlation between the extracted commercial product technology elements and application problem characteristics and filling them into a preset matrix framework, the constructed product technology and bottleneck matrix not only clearly presents the matching gap between existing technical solutions and actual market needs, but also transforms fragmented market feedback information into a structured data model that can be quantified and analyzed. This provides a reliable business dimension input for subsequent identification of market-driven technology opportunities and positioning of product iteration and innovation directions. It effectively solves the dilemma of traditional market analysis being mainly qualitative descriptions and difficult to directly correlate with technology R&D data, and significantly improves the market orientation and commercial value of technology opportunity identification results.

[0043] In one implementation, such as Figure 4 The patent technology opportunity identification algorithm described above is used to identify patent technology opportunities in the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix, generating a patent technology opportunity list, including: Obtain a matrix of patent technologies and their effectiveness, a matrix of non-patent literature technologies and their problems, and a matrix of product technologies and their bottlenecks within the same technology subfield; A blank opportunity identification algorithm is used to calculate blank opportunity scores for the patent technology and efficacy matrix, non-patent literature technology and problem matrix, and product technology and bottleneck matrix in the same technology subfield, and to identify blank patent technology opportunities based on the blank opportunity scores. An alternative opportunity identification algorithm is used to identify existing solutions and alternative paths for each problem in the patent technology and efficacy matrix, non-patent literature technology and problem matrix, and product technology and bottleneck matrix of the same technology subfield, and to identify alternative patent technology opportunities based on the existing solutions and alternative paths. An evolutionary opportunity identification algorithm is used to calculate the evolutionary opportunity scores of the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix in the same technology subfield. Based on the evolutionary opportunity scores, evolutionary patent technology opportunities are identified. Based on the aforementioned blank patent technology opportunities, alternative patent technology opportunities, and evolutionary patent technology opportunities, a list of patent technology opportunities is generated. This invention constructs a three-in-one algorithm identification system to collaboratively analyze three structured matrices within the same technology subfield: First, a blank opportunity identification algorithm is used to generate blank opportunity scores, accurately locating technology gaps with sparse patent layout but high research attention and urgent market demand; second, an alternative opportunity identification algorithm is used to systematically analyze existing solutions and alternative paths corresponding to each technical problem in the three matrices, discovering improvement opportunities to bypass existing patent barriers; simultaneously, an evolutionary opportunity identification algorithm is used to calculate evolutionary opportunity scores, predicting future trends and upgrade directions of technological development; finally, the three types of identification results are deduplicated, fused, and prioritized to generate a structured list of patent technology opportunities. This multi-algorithm collaborative identification mechanism effectively overcomes the limitations of a single analytical perspective, ensuring coverage of opportunities across the entire innovation chain from basic research to commercial applications, and providing differentiated guidance for R&D decisions through quantitative scoring and path analysis, significantly improving the comprehensiveness, accuracy, and strategic value of technology opportunity discovery.

[0044] In one implementation, a blank opportunity identification algorithm is used to calculate blank opportunity scores for the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix within the same technology subfield. Based on the blank opportunity scores, blank patent technology opportunities are identified, including: A three-dimensional feature space of technology-efficacy-problem is constructed with technical parameters, efficacy parameters, and problem parameters as axes; the three-dimensional feature space of technology-efficacy-problem includes multiple technical units; For example, the X-axis represents specific technical means or solutions, with technical parameters as the X-axis. The technical nodes on this axis are constructed by combining international patent classifications or joint patent classifications with technical dictionaries to ensure the scientific validity and consistency of the classification. For instance, in the field of "battery technology," technical nodes might include "solid-state electrolyte," "silicon-based anode," and "fast-charging management circuit." The Y-axis represents the functional effects that the technology can achieve. Functional nodes are derived from text mining of patent claims and product specifications, such as "increased energy density," "extended cycle life," and "enhanced safety." The Z-axis represents the technical challenges that urgently need to be addressed in scientific literature and the product market. Problem nodes are extracted from non-patent literature abstracts and user feedback data, such as "lithium dendrite growth," "capacity decay at high temperatures," and "low charging efficiency."

[0045] The technical means characteristics and functional efficacy information characteristics of each pair in the patent technology and efficacy matrix of the same technical subfield, the cutting-edge technical point characteristics and scientific problem characteristics of each pair in the non-patent literature technology and problem matrix, and the commercial product technology element characteristics and application problem characteristics of each pair in the product technology and bottleneck matrix are respectively mapped into the three-dimensional feature space of technology-efficacy-problem. For example, each "technology-efficacy" pair in the patent technology and efficacy matrix is ​​mapped to a patent data point in the three-dimensional feature space of technology-efficacy-problem, with its weight being the quantity or quality of patents under that technology route (such as citation frequency); each "technology-problem" pair in the non-patent literature technology and problem matrix is ​​mapped to a literature data point in the three-dimensional feature space of technology-efficacy-problem, with its weight being the quantity or influence factor of relevant research literature; each "technology-bottleneck" pair in the product technology and bottleneck matrix is ​​mapped to a product data point in the three-dimensional feature space of technology-efficacy-problem, with its weight being the frequency or severity of the bottleneck in product market feedback; through this mapping, the originally fragmented three types of data are integrated into a unified, quantifiable analytical framework.

[0046] After scanning and determining the patent data points, literature data points, and product data points of each technical unit in the three-dimensional feature space of technology-efficacy-problem, the patent gap degree, literature problem concentration degree, and product bottleneck intensity are determined based on the patent data points, literature data points, and product data points. For example, patent gap essentially measures the degree of lack of patent protection at a specific intersection of "technology-efficacy-problem"; for a given technology unit, the sum of the number and weights of patent points within it is calculated; literature problem concentration essentially measures the level of attention the scientific community pays to problems related to that technology unit. High attention and low patent coverage indicate a cutting-edge research gap, and the sum of the number and weights of non-patent literature points within that technology unit is calculated. Concentration is positively correlated with this value. This indicates that the scientific community has identified this as a problem worth studying; the technical essence of product bottleneck strength is to measure the severity of the problem faced by the market in that technology unit. High strength indicates a clear market demand and commercial potential, and the sum of the weights of product bottleneck points within that technology unit is calculated. Strength is positively correlated with this value. This directly reflects the market value that solving the problem can bring; these weights are not fixed and can be optimized using the Delphi method by industry experts or machine learning models based on historical successful technology opportunity cases. For example, in technology-driven fields (such as new materials), weights A and B may be higher; in market-driven fields (such as consumer electronics), weight C may be set higher.

[0047] Based on the patent vacancy rate, the concentration of literature issues, and the product bottleneck intensity and their corresponding weights, a blank opportunity score is calculated for each technology unit. When the blank opportunity score exceeds a preset threshold and the technical feasibility assessment meets the standard, the content of the corresponding technology unit is marked as a blank patent technology opportunity. For example, a high blank opportunity score alone is insufficient to qualify as a viable "opportunity." Feasibility filtering is also required. This threshold is determined by analyzing the score distribution of successful technological opportunities in historical data, used to filter out highly significant blanks. Technical feasibility assessment filters out nodes that "appear to be opportunities but are actually difficult to implement." The assessment includes: technological relevance, evaluating the relevance between the blank and existing mature technologies. If the technology required to achieve the blank differs significantly from existing technologies, feasibility is low; and implementation difficulty assessment, based on experimental data from relevant non-patent literature, evaluating the estimated difficulty in solving the problem in terms of materials, processes, and costs. Only when both a high blank score and technical feasibility conditions are met will the system officially mark it as a valuable and feasible blank patent technology opportunity and include it in the final opportunity list.

[0048] The technical unit consists of a unique technology, efficacy, and problem; In one implementation, the blank opportunity score is calculated as follows:

[0049] in, Rate the blank opportunity. For patent gaps, As a weight for patent vacancy, For the concentration of literature questions, The weight of the concentration of literature questions, For product bottleneck strength, The weighting of the bottleneck strength of the product.

[0050] In one implementation, an alternative opportunity identification algorithm is employed to identify existing solutions and alternative paths for each problem in the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix within the same technology subfield. Based on the existing solutions and alternative paths, alternative patent technology opportunities are identified, including: From the patent technology and efficacy matrix of the same technology subfield, technical means that match the application problems in the product technology and bottleneck matrix are retrieved to generate a set of existing technical solutions; the set of existing technical solutions includes multiple existing technical solutions. For example, using specific "application problem characteristics" identified in the product technology and bottleneck matrix as search clues, a matching query is performed in the patent technology and efficacy matrix to find patent technology solutions that correspond or directly match the "application problem characteristics" in terms of "functional efficacy information characteristics." This forms a set of existing technology solutions, where each solution represents the mainstream or known technology currently protected by patents in the market for solving the application problem. This step clarifies the scope of existing patent protection that needs to be circumvented or improved, setting a target for finding alternative paths.

[0051] In the non-patent literature technology and problem matrix, cutting-edge technology points that can solve the application problem are retrieved to generate a set of candidate alternative paths; the set of candidate alternative paths includes multiple candidate alternative path schemes. For example, for the same "application problem feature", a search is performed in the non-patent literature technology and problem matrix to find "cutting-edge technology features" that match or are highly related to the "application problem feature" in terms of "scientific problem feature". This forms a set of candidate alternative paths, where each solution represents a new idea, principle or technology proposed in the scientific research field that may not yet be fully covered by patents to solve the problem. This step uncovers potential technological breakthroughs from the forefront of scientific research and provides a candidate library for circumventing existing patents and achieving technological transcendence.

[0052] Based on the technical path differences between existing technical solutions and corresponding candidate alternative solutions, calculate the substitution potential index of candidate alternative solutions; For example, this is the core of the algorithm's quantization, designed to objectively evaluate the substitution value of each candidate alternative path relative to existing technological solutions. Its calculation is based on the following formula:

[0053] in, This is an index representing the alternative potential of candidate alternative pathways. The composite function of the weighted geometric mean, To differentiate the technical approaches, To improve efficacy, This is a cost optimization coefficient; The technical path difference essentially measures the fundamental difference between the candidate path and the existing technology in terms of technical principles and implementation methods. The greater the difference, the higher the possibility of avoiding patent infringement. Calculation method: Using natural language processing technology, extract the technical feature vectors of the existing technical solution and the corresponding candidate alternative path solution, and calculate the cosine similarity; Technical path difference D = 1 - cosine similarity; When the two technical descriptions are completely unrelated, D approaches 1. The efficiency improvement rate essentially measures the extent to which the candidate path improves performance, efficiency, and effectiveness compared to existing technologies. The calculation method is as follows:

[0054] in, To improve efficacy, For the j-th candidate alternative path, For the corresponding i-th existing technical solution, the key performance indicators are: The cost optimization coefficient essentially measures the optimization potential of candidate paths in terms of manufacturing costs, material costs, or operating costs; it is estimated based on text analysis or extracted from data; C can be normalized to the range of [-1, 1], with positive values ​​indicating cost reduction.

[0055] When the substitution potential index is greater than the industry benchmark and there is technological substitution feasibility, the corresponding candidate substitution path scheme is marked as a substitute patent technology opportunity.

[0056] For example, this benchmark is determined by retrospectively analyzing successful technology substitution cases in the field to ensure that the selected opportunities have significant potential. The technology substitution feasibility assessment is an auxiliary analysis that evaluates the feasibility of candidate paths in terms of technology maturity, engineering implementation difficulty, and supply chain support, filtering out solutions that are currently difficult to implement. The system officially marks the candidate substitution path as a substitute patent technology opportunity only when both of the above conditions are met, and suggests innovation layout and patent application around this path. Through the above-mentioned progressive algorithm steps, this invention transforms the identification of substitution opportunities from a random process that relies on the inspiration and experience of R&D personnel into a systematic, data-driven, quantifiable, and automated analysis process, significantly improving the efficiency and success rate of enterprises in finding technological breakthroughs.

[0057] In one implementation, an evolutionary opportunity identification algorithm is employed to calculate evolutionary opportunity scores for the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix within the same technology subfield. Based on these evolutionary opportunity scores, evolutionary patent technology opportunities are identified, including: Extract the next-generation technology direction from the iterative plan of the product technology and bottleneck matrix in the same technology subfield; For example, this approach focuses on extracting "iteration plan" data from product technology and bottleneck matrices within the same technology subfield. Using natural language processing and text mining techniques, it identifies keywords and phrases representing future technological directions from the text descriptions of these iteration plans. Examples include identifying future tense or planning-oriented guiding words such as "next generation," "planned," "expected adoption," and "goal achieved." The subsequent technical noun phrases following these guiding words, such as "all-solid-state battery architecture," are extracted to form a set of next-generation technology directions, representing the future development path planned by the industry based on current market and technological understanding.

[0058] The next-generation technology direction is cross-validated and reverse-mapped with the cutting-edge technology points of the non-patent literature technology and problem matrix to generate multiple iterative technologies; For example, cross-validation of technical paths involves using each "next-generation technology direction" as a query condition, searching and matching it in a non-patent literature technology and problem matrix, and analyzing whether there are already cutting-edge technology points (such as principle verification, experimental data, and model simulation) in scientific research literature that support the realization of this direction. The degree of technical relevance is calculated; for example, by comparing the technical feature vectors of the two, the cosine similarity is calculated, and "technical direction-cutting-edge technology point" pairs with a technical relevance higher than a preset threshold are selected to ensure that the enterprise's planning has a scientific basis. Reverse mapping transforms the validated "technical direction-cutting-edge technology point" pairs into specific and implementable technical solutions. The mapping logic is based on the experimental schemes, structural designs, or algorithm steps disclosed in the cutting-edge technology points, combined with the macro-goals of the next-generation technology direction, to construct one or more "iterative technology" solutions with complete technical means. For example, pairing "all-solid-state battery architecture" with "sulfide electrolyte interface stabilization technology" in the literature results in "a method for optimizing the interface of all-solid-state batteries based on sulfide electrolytes."

[0059] For each iterative technology, a technological evolution projection is performed. During the projection process, the technological growth rate, efficiency leap probability, and market demand matching degree of each iterative technology are extracted, and a technological evolution opportunity score for each iterative technology is calculated. For example, for each generated iterative technique, a dynamic and quantitative potential assessment is performed. The formula for calculating the technology evolution opportunity score is as follows:

[0060] in, Rate the opportunities for technological evolution. For the speed of technological growth, For the probability of efficiency transition, To match market demand; The technology growth rate measures the activity and development momentum of the technological field in which the iterative technology operates. In the time-series data of the patent technology and efficacy matrix, the compound annual growth rate (CAGR) of patents related to the iterative technology in recent years is statistically analyzed. A higher V-value indicates that the field is on the verge of explosive growth or in a rapid growth phase. The efficacy leap probability measures the likelihood that the iterative technology will achieve a breakthrough in core performance indicators compared to existing technologies. Based on experimental data reported in relevant literature in the non-patent literature technology and problem matrix, statistical methods (such as Monte Carlo simulation) are used to predict the probability that its performance indicators will surpass the current mainstream technology level. For example, calculating the probability that its energy density will reach 500Wh / kg. Market demand matching degree measures the degree of alignment between the improved efficacy of the iterative technology and the core market demands reflected in the product technology and bottleneck matrix. The calculation formula for market demand matching degree is as follows:

[0061] in, To match market demand, Weighting of the effectiveness of technological advancements The intensity of market demand for this effect; Demand intensity can be extracted from market feedback through methods such as sentiment analysis and word frequency statistics.

[0062] Based on the aforementioned technology evolution opportunity score, iterative technologies that are in the technology growth stage and have the characteristics of efficiency leaps are identified and marked as evolutionary patent technology opportunities.

[0063] For example, when the score E is higher than the domain threshold learned from historical data, and the technology growth rate V is greater than zero, it indicates that the technology life cycle is in its nascent or growth stage, and the probability of a leap in effectiveness P is higher than a high threshold (e.g., 0.7), indicating that the technology is not an incremental improvement but has breakthrough potential. When all three conditions are met, the system marks the iterative technology as an evolutionary patent technology opportunity. This shows that the technology direction not only conforms to industrial planning and scientific research trends but also has strong market momentum and disruptive potential, making it the best target for forward-looking patent layout. Through the above algorithm, this invention transforms technology foresight from a qualitative activity relying on expert intuition into a data-driven, computable, and repeatable automated analysis process, providing scientific decision support for enterprises to seize future technological high ground.

[0064] Example 2: Based on the same inventive concept, this patent application also provides a patent technology opportunity identification system, such as... Figure 5 As shown, it includes: an opportunity identification basic data extraction module, a matrix construction module, and a patent technology opportunity list generation module; The opportunity identification basic data extraction module is used to extract opportunity identification basic data in the target technology field from the patent database, non-patent literature database and product market database respectively. The matrix construction module is used to construct, based on the opportunity identification basic data, a patent technology and efficacy matrix, a non-patent literature technology and problem matrix, and a product technology and bottleneck matrix, respectively. The patent technology opportunity list generation module is used to identify patent technology opportunities in the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix by using a patent technology opportunity identification algorithm, and generate a patent technology opportunity list.

[0065] In one implementation, the opportunity identification basic data extraction module is specifically used for: Retrieve patent texts in the target technical field from the patent database, and extract the classification number, invention title, specification, and claims of the patent texts; In non-patent literature databases, retrieve articles corresponding to the patent text, and extract the abstract, keywords, main text, introduction, and conclusion of the articles; In the product market database, retrieve the product market data corresponding to the patent text, and extract the technical summary, technical route, iteration plan, manufacturer's self-description, and market feedback of the product market data; The classification number, invention title, specification, claims, abstract, keywords, main text, introduction, conclusion, technical overview, technical route, iteration plan, manufacturer's statement, and market feedback are cleaned and standardized to serve as the basis for opportunity identification.

[0066] In one implementation, the system further includes: a patent article product corresponding module; the patent article product corresponding module is used for: Using the main classification number of the patent text as the technical classification identifier, patent texts with the same classification number or patent texts with the same first four classification numbers are classified into the same technical subfield. Based on the keywords of the articles, each article is divided into a corresponding technical subfield; Based on the technical overview of the product market data, each product is categorized into its corresponding technical subfield.

[0067] In one implementation, the matrix construction module includes: The patent technology and efficacy matrix construction submodule is used to extract technical means features and corresponding functional efficacy information features from the opportunity identification basic data corresponding to the patent text, and construct the patent technology and efficacy matrix. The non-patent literature technology and problem matrix construction submodule is used to extract cutting-edge technology features and scientific problem features from the opportunity identification basic data corresponding to the articles, and construct the non-patent literature technology and problem matrix. The product technology and bottleneck matrix construction submodule is used to extract the characteristics of commercial product technology elements and application problem characteristics from the opportunity identification basic data corresponding to the product market data, and construct the product technology and bottleneck matrix.

[0068] In one implementation, the patent technology and efficacy matrix construction submodule is specifically used for: Set up a first two-dimensional matrix with technical means features as rows and functional and efficacy information features as columns; From the claims of the opportunity identification basic data corresponding to the patent text, extract the core technical features and specific structures, components, materials, and process steps of the patent text as technical means features; Information describing the technical effects is extracted from the specification of the opportunity identification basic data corresponding to the patent text and used as functional efficacy information features. The extracted technical features and functional efficacy information features are filled into the first two-dimensional matrix to construct the patent technology and efficacy matrix.

[0069] In one implementation, the non-patent literature technology and problem matrix construction submodule is specifically used for: Set up a second two-dimensional matrix with features of cutting-edge technologies as rows and features of scientific questions as columns; From the summary, keywords, and main text of the opportunity identification basic data corresponding to the article, extract the novel methods, new materials, unique structures, improved algorithms, or innovative experimental schemes of the article as features of cutting-edge technologies; Extract the core scientific challenges or technical bottlenecks of the article from the abstract, introduction, and conclusion of the opportunity identification basic data corresponding to the article, and use them as the features of the scientific problem. The extracted cutting-edge technology features and scientific problem features are filled into the second two-dimensional matrix to construct a non-patent literature technology and problem matrix.

[0070] In one implementation, the product technology and bottleneck matrix construction submodule is specifically used for: Set up a third two-dimensional matrix with the technical features of commercial products as rows and the application problems of products as columns; From the technical overview, technical roadmap, and iteration plan of the opportunity identification basic data corresponding to the product market data, mature technical solutions of the product market data are extracted as technical element features of commercial products. The application problem characteristics of the product are extracted from the manufacturer's self-report, iteration plan and market feedback from the opportunity identification basic data corresponding to the product market data; The extracted commercial product technology elements and product application problems are filled into the third two-dimensional matrix to construct the product technology and bottleneck matrix.

[0071] In one implementation, the patent opportunity list generation module includes: The patent article product extraction submodule is used to obtain the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix in the same technology subfield. The blank patent technology opportunity identification submodule is used to calculate the blank opportunity score of the patent technology and efficacy matrix, non-patent literature technology and problem matrix and product technology and bottleneck matrix in the same technology subfield using the blank opportunity identification algorithm, and to identify blank patent technology opportunities based on the blank opportunity score. The alternative patent technology opportunity identification submodule is used to identify existing solutions and alternative paths for each problem in the patent technology and efficacy matrix, non-patent literature technology and problem matrix, and product technology and bottleneck matrix of the same technology subfield using an alternative opportunity identification algorithm, and to identify alternative patent technology opportunities based on the existing solutions and alternative paths. The evolutionary patent technology opportunity identification submodule is used to calculate the evolutionary opportunity score of the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix in the same technology subfield using the evolutionary opportunity identification algorithm, and to identify evolutionary patent technology opportunities based on the evolutionary opportunity score. The patent technology opportunity list generation submodule is used to generate a patent technology opportunity list based on the blank patent technology opportunities, the alternative patent technology opportunities, and the evolutionary patent technology opportunities.

[0072] In one implementation, the blank patent technology opportunity identification submodule is specifically used for: A three-dimensional feature space of technology-efficacy-problem is constructed with technical parameters, efficacy parameters, and problem parameters as axes; the three-dimensional feature space of technology-efficacy-problem includes multiple technical units; The technical means characteristics and functional efficacy information characteristics of each pair in the patent technology and efficacy matrix of the same technical subfield, the cutting-edge technical point characteristics and scientific problem characteristics of each pair in the non-patent literature technology and problem matrix, and the commercial product technology element characteristics and application problem characteristics of each pair in the product technology and bottleneck matrix are respectively mapped into the three-dimensional feature space of technology-efficacy-problem. After scanning and determining the patent data points, literature data points, and product data points of each technical unit in the three-dimensional feature space of technology-efficacy-problem, the patent gap degree, literature problem concentration degree, and product bottleneck intensity are determined based on the patent data points, literature data points, and product data points. Based on the patent vacancy rate, the concentration of literature issues, and the product bottleneck intensity and their corresponding weights, a blank opportunity score is calculated for each technology unit. When the blank opportunity score exceeds a preset threshold and the technical feasibility assessment meets the standard, the content of the corresponding technology unit is marked as a blank patent technology opportunity. The technical unit consists of a unique technology, efficacy, and problem.

[0073] In one implementation, the blank opportunity score is calculated as follows:

[0074] in, Rate the blank opportunity. For patent gaps, As a weight for patent vacancy, For the concentration of literature questions, The weight of the concentration of literature questions, For product bottleneck strength, The weighting of the bottleneck strength of the product.

[0075] In one implementation, the alternative patent technology opportunity identification submodule is specifically used for: From the patent technology and efficacy matrix of the same technology subfield, technical means that match the application problems in the product technology and bottleneck matrix are retrieved to generate a set of existing technical solutions; the set of existing technical solutions includes multiple existing technical solutions. In the non-patent literature technology and problem matrix, cutting-edge technology points that can solve the application problem are retrieved to generate a set of candidate alternative paths; the set of candidate alternative paths includes multiple candidate alternative path schemes. Analyze the technical path differences between existing technical solutions and corresponding candidate alternative solutions, and calculate the substitution potential index of candidate alternative solutions; When the substitution potential index is greater than the industry benchmark and there is technological substitution feasibility, the corresponding candidate substitution path scheme is marked as a substitute patent technology opportunity.

[0076] In one implementation, the evolutionary patent technology opportunity identification submodule is specifically used for: Extract the next-generation technology direction from the iterative plan of the product technology and bottleneck matrix in the same technology subfield; The next-generation technology direction is cross-validated and reverse-mapped with the cutting-edge technology points of the non-patent literature technology and problem matrix to generate multiple iterative technologies; For each iterative technology, a technological evolution projection is performed. During the projection process, the technological growth rate, efficiency leap probability, and market demand matching degree of each iterative technology are extracted, and a technological evolution opportunity score for each iterative technology is calculated. Based on the aforementioned technology evolution opportunity score, iterative technologies that are in the technology growth stage and have the characteristics of efficiency leaps are identified and marked as evolutionary patent technology opportunities.

[0077] Example 3 like Figure 6 As shown, the present invention also provides an electronic device, which may be a computer device, a microcontroller device, a smart mobile device, etc. The electronic device in this embodiment may include a processor, a memory, a transceiver component, etc. The memory, processor, and transceiver component are connected via a bus; the memory can be used to store executable programs, and an exemplary executable program may include instructions; the processor is used to execute the instructions stored in the memory. The memory can also be used to store data, which can be accessed and / or modified when instructions are executed.

[0078] The processor may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and it is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions in the storage medium to implement the corresponding method flow or corresponding function, so as to implement the steps of the patented technology opportunity identification method in the above embodiments.

[0079] Example 4 Based on the same inventive concept, this invention also provides a readable storage medium, specifically an electronic device readable storage medium (Memory). This readable storage medium is a memory device within an electronic device used to store programs and data. It is understood that the storage medium here can include both built-in storage media within the electronic device and extended storage media supported by the electronic device. The storage medium provides storage space, which stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more executable programs (including program code). It should be noted that the storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. Loading and executing one or more instructions stored in the storage medium by the processor can implement the steps of the patented technology opportunity identification method described in the above embodiments.

[0080] Those skilled in the art will understand that embodiments of this patent application can be provided as methods, systems, or computer program products. Therefore, this patent application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this patent application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0081] This patent application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the patent application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0082] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1The function specified in one or more boxes.

[0083] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0084] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this patent application and not to limit its scope of protection. Although the patent application has been described in detail with reference to the above embodiments, those skilled in the art should understand that after reading this patent application, they can still make various changes, modifications or equivalent substitutions to the specific implementation of the application, but these changes, modifications or equivalent substitutions are all within the scope of protection of the claims pending approval.

Claims

1. A method for identifying patent technology opportunities, characterized in that, include: Basic data for opportunity identification in the target technology field were extracted from patent databases, non-patent literature databases, and product market databases, respectively. Based on the aforementioned opportunity identification data, a patent technology and efficacy matrix, a non-patent literature technology and problem matrix, and a product technology and bottleneck matrix are constructed respectively. A patent technology opportunity identification algorithm is used to identify patent technology opportunities in the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix, and generate a patent technology opportunity list. The patent technology opportunity identification algorithm is used to identify patent technology opportunities in the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix, generating a patent technology opportunity list, including: Obtain a matrix of patent technologies and their effectiveness, a matrix of non-patent literature technologies and their problems, and a matrix of product technologies and their bottlenecks within the same technology subfield; A blank opportunity identification algorithm is used to calculate blank opportunity scores for the patent technology and efficacy matrix, non-patent literature technology and problem matrix, and product technology and bottleneck matrix in the same technology subfield, and to identify blank patent technology opportunities based on the blank opportunity scores. An alternative opportunity identification algorithm is used to identify existing solutions and alternative paths for each problem in the patent technology and efficacy matrix, non-patent literature technology and problem matrix, and product technology and bottleneck matrix of the same technology subfield, and to identify alternative patent technology opportunities based on the existing solutions and alternative paths. An evolutionary opportunity identification algorithm is used to calculate the evolutionary opportunity scores of the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix in the same technology subfield. Based on the evolutionary opportunity scores, evolutionary patent technology opportunities are identified. A list of patent opportunities is generated based on the blank patent opportunities, the alternative patent opportunities, and the evolutionary patent opportunities.

2. The method as described in claim 1, characterized in that, The extraction of opportunity identification basic data from patent databases, non-patent literature databases, and product market databases, respectively, includes: Retrieve patent texts in the target technical field from the patent database, and extract the classification number, invention title, specification, and claims of the patent texts; In non-patent literature databases, retrieve articles corresponding to the patent text, and extract the abstract, keywords, main text, introduction, and conclusion of the articles; In the product market database, retrieve the product market data corresponding to the patent text, and extract the technical summary, technical route, iteration plan, manufacturer's self-description, and market feedback of the product market data; The classification number, invention title, specification, claims, abstract, keywords, main text, introduction, conclusion, technical overview, technical route, iteration plan, manufacturer's statement, and market feedback are cleaned and standardized to serve as the basis for opportunity identification.

3. The method as described in claim 2, characterized in that, After extracting opportunity identification basic data for the target technology field from the patent database, non-patent literature database, and product market database respectively, and before constructing the patent technology and efficacy matrix, non-patent literature technology and problem matrix, and product technology and bottleneck matrix based on the opportunity identification basic data respectively, the following further includes: Using the main classification number of the patent text as the technical classification identifier, patent texts with the same classification number or patent texts with the same first four classification numbers are classified into the same technical subfield. Based on the keywords of the articles, each article is divided into a corresponding technical subfield; Based on the technical overview of the product market data, each product is categorized into its corresponding technical subfield.

4. The method as described in claim 2, characterized in that, Based on the opportunity identification data, the following matrices are constructed: a patent technology and efficacy matrix, a non-patent literature technology and problem matrix, and a product technology and bottleneck matrix, including: From the opportunity identification basic data corresponding to the patent text, technical means features and corresponding functional efficacy information features are extracted to construct a patent technology and efficacy matrix. From the opportunity identification basic data corresponding to the articles, we extract the features of cutting-edge technology points and scientific questions to construct a non-patent literature technology and question matrix. From the opportunity identification base data corresponding to the product market data, extract the technical element characteristics and application problem characteristics of commercial products, and construct a product technology and bottleneck matrix.

5. The method as described in claim 4, characterized in that, The step of extracting technical means features and corresponding functional efficacy information features from the opportunity identification basic data corresponding to the patent text, and constructing a patent technology and efficacy matrix, includes: Set up a first two-dimensional matrix with technical means features as rows and functional efficacy information features as columns; From the claims of the opportunity identification basic data corresponding to the patent text, extract the core technical features and specific structures, components, materials, and process steps of the patent text as technical means features; Information describing the technical effects is extracted from the specification of the opportunity identification basic data corresponding to the patent text and used as functional efficacy information features. The extracted technical features and functional efficacy information features are filled into the first two-dimensional matrix to construct the patent technology and efficacy matrix.

6. The method as described in claim 4, characterized in that, The step of extracting cutting-edge technology features and scientific question features from the opportunity identification basic data corresponding to the article, and constructing a non-patent literature technology and question matrix, includes: Set up a second two-dimensional matrix with cutting-edge technology features as rows and scientific question features as columns; From the summary, keywords, and main text of the opportunity identification basic data corresponding to the article, extract the novel methods, new materials, unique structures, improved algorithms, or innovative experimental schemes of the article as features of cutting-edge technologies; Extract the core scientific challenges or technical bottlenecks of the article from the abstract, introduction, and conclusion of the opportunity identification basic data corresponding to the article, and use them as the features of the scientific problem. The extracted cutting-edge technology features and scientific problem features are filled into the second two-dimensional matrix to construct a non-patent literature technology and problem matrix.

7. The method as described in claim 4, characterized in that, The step of extracting commercial product technology element characteristics and application problem characteristics from the opportunity identification basic data corresponding to the product market data, and constructing a product technology and bottleneck matrix, includes: Set up a third two-dimensional matrix with the technical features of commercial products as rows and the application problems of products as columns; From the technical overview, technical roadmap, and iteration plan of the opportunity identification basic data corresponding to the product market data, mature technical solutions of the product market data are extracted as technical element features of commercial products. The application problem characteristics of the product are extracted from the manufacturer's self-report, iteration plan, and market feedback, which are the basic data for opportunity identification corresponding to the product market data. The extracted commercial product technology elements and product application problems are filled into the third two-dimensional matrix to construct the product technology and bottleneck matrix.

8. The method as described in claim 1, characterized in that, The algorithm employs a blank opportunity identification method to calculate blank opportunity scores for the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix within the same technology subfield. Based on these blank opportunity scores, blank patent technology opportunities are identified, including: A three-dimensional feature space of technology-efficacy-problem is constructed with technical parameters, efficacy parameters, and problem parameters as axes; the three-dimensional feature space of technology-efficacy-problem includes multiple technical units; The technical means characteristics and functional efficacy information characteristics of each pair in the patent technology and efficacy matrix of the same technical subfield, the cutting-edge technical point characteristics and scientific problem characteristics of each pair in the non-patent literature technology and problem matrix, and the commercial product technology element characteristics and application problem characteristics of each pair in the product technology and bottleneck matrix are respectively mapped into the three-dimensional feature space of technology-efficacy-problem. After scanning and determining the patent data points, literature data points, and product data points of each technical unit in the three-dimensional feature space of technology-efficacy-problem, the patent gap degree, literature problem concentration degree, and product bottleneck intensity are determined based on the patent data points, literature data points, and product data points. Based on the patent vacancy rate, the concentration of literature issues, and the product bottleneck intensity and their corresponding weights, a blank opportunity score is calculated for each technology unit. When the blank opportunity score exceeds a preset threshold and the technical feasibility assessment meets the standard, the content of the corresponding technology unit is marked as a blank patent technology opportunity. The technical unit consists of a unique technology, efficacy, and problem.

9. The method as described in claim 8, characterized in that, The formula for calculating the blank opportunity score is as follows: in, Rate the blank opportunity. For patent gaps, As a weight for patent vacancy, For the concentration of literature questions, The weight of the concentration of literature questions, For product bottleneck strength, The weighting of the bottleneck strength of the product.

10. The method as described in claim 1, characterized in that, The algorithm employs an alternative opportunity identification method to identify existing solutions and alternative paths for each problem in the patent technology and efficacy matrix, non-patent literature technology and problem matrix, and product technology and bottleneck matrix within the same technology subfield. Based on these existing solutions and alternative paths, it identifies alternative patent technology opportunities, including: From the patent technology and efficacy matrix of the same technology subfield, technical means that match the application problems in the product technology and bottleneck matrix are retrieved to generate a set of existing technical solutions; the set of existing technical solutions includes multiple existing technical solutions. In the non-patent literature technology and problem matrix, cutting-edge technology points that can solve the application problem are retrieved to generate a set of candidate alternative paths; the set of candidate alternative paths includes multiple candidate alternative path schemes. Based on the technical path differences between existing technical solutions and corresponding candidate alternative solutions, calculate the substitution potential index of candidate alternative solutions; When the substitution potential index is greater than the industry benchmark and there is technological substitution feasibility, the corresponding candidate substitution path scheme is marked as a substitute patent technology opportunity.

11. The method as described in claim 1, characterized in that, The method employs an evolutionary opportunity identification algorithm to calculate evolutionary opportunity scores for the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix within the same technology subfield. Based on these evolutionary opportunity scores, evolutionary patent technology opportunities are identified, including: Extract the next-generation technology direction from the iterative plan of the product technology and bottleneck matrix in the same technology subfield; The next-generation technology direction is cross-validated and reverse-mapped with the cutting-edge technology points of the non-patent literature technology and problem matrix to generate multiple iterative technologies; For each iterative technology, a technological evolution projection is performed. During the projection process, the technological growth rate, efficiency leap probability, and market demand matching degree of each iterative technology are extracted, and a technological evolution opportunity score for each iterative technology is calculated. Based on the aforementioned technology evolution opportunity score, iterative technologies that are in the technology growth stage and have the characteristics of efficiency leaps are identified and marked as evolutionary patent technology opportunities.

12. A patented technology opportunity recognition system, characterized in that, include: The module includes an opportunity identification basic data extraction module, a matrix construction module, and a patent technology opportunity list generation module. The opportunity identification basic data extraction module is used to extract opportunity identification basic data in the target technology field from the patent database, non-patent literature database and product market database respectively. The matrix construction module is used to construct, based on the opportunity identification basic data, a patent technology and efficacy matrix, a non-patent literature technology and problem matrix, and a product technology and bottleneck matrix, respectively. The patent technology opportunity list generation module is used to use a patent technology opportunity identification algorithm to identify patent technology opportunities in the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix, and generate a patent technology opportunity list. The patent technology opportunity list generation module includes: The patent article product extraction submodule is used to obtain the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix in the same technology subfield. The blank patent technology opportunity identification submodule is used to calculate the blank opportunity score of the patent technology and efficacy matrix, non-patent literature technology and problem matrix and product technology and bottleneck matrix in the same technology subfield using the blank opportunity identification algorithm, and to identify blank patent technology opportunities based on the blank opportunity score. The alternative patent technology opportunity identification submodule is used to identify existing solutions and alternative paths for each problem in the patent technology and efficacy matrix, non-patent literature technology and problem matrix, and product technology and bottleneck matrix of the same technology subfield using an alternative opportunity identification algorithm, and to identify alternative patent technology opportunities based on the existing solutions and alternative paths. The evolutionary patent technology opportunity identification submodule is used to calculate the evolutionary opportunity score of the patent technology and efficacy matrix, the non-patent literature technology and problem matrix, and the product technology and bottleneck matrix in the same technology subfield using the evolutionary opportunity identification algorithm, and to identify evolutionary patent technology opportunities based on the evolutionary opportunity score. The patent technology opportunity list generation submodule is used to generate a patent technology opportunity list based on the blank patent technology opportunities, the alternative patent technology opportunities, and the evolutionary patent technology opportunities.

13. The system as described in claim 12, characterized in that, The opportunity recognition basic data extraction module is specifically used for: Retrieve patent texts in the target technical field from the patent database, and extract the classification number, invention title, specification, and claims of the patent texts; In non-patent literature databases, retrieve articles corresponding to the patent text, and extract the abstract, keywords, main text, introduction, and conclusion of the articles; In the product market database, retrieve the product market data corresponding to the patent text, and extract the technical summary, technical route, iteration plan, manufacturer's self-description, and market feedback of the product market data; The classification number, invention title, specification, claims, abstract, keywords, main text, introduction, conclusion, technical overview, technical route, iteration plan, manufacturer's statement, and market feedback are cleaned and standardized to serve as the basis for opportunity identification.

14. The system as described in claim 13, characterized in that, The system further includes: a patent article product corresponding module; the patent article product corresponding module is used for: Using the main classification number of the patent text as the technical classification identifier, patent texts with the same classification number or patent texts with the same first four classification numbers are classified into the same technical subfield. Based on the keywords of the articles, each article is divided into a corresponding technical subfield; Based on the technical overview of the product market data, each product is categorized into its corresponding technical subfield.

15. The system as described in claim 13, characterized in that, The matrix construction module includes: The patent technology and efficacy matrix construction submodule is used to extract technical means features and corresponding functional efficacy information features from the opportunity identification basic data corresponding to the patent text, and construct the patent technology and efficacy matrix. The non-patent literature technology and problem matrix construction submodule is used to extract cutting-edge technology features and scientific problem features from the opportunity identification basic data corresponding to the articles, and construct the non-patent literature technology and problem matrix. The product technology and bottleneck matrix construction submodule is used to extract the characteristics of commercial product technology elements and application problem characteristics from the opportunity identification basic data corresponding to the product market data, and construct the product technology and bottleneck matrix.

16. The system as described in claim 15, characterized in that, The patent technology and efficacy matrix construction submodule is specifically used for: Set up a first two-dimensional matrix with technical means features as rows and functional efficacy information features as columns; From the claims of the opportunity identification basic data corresponding to the patent text, extract the core technical features and specific structures, components, materials, and process steps of the patent text as technical means features; Information describing the technical effects is extracted from the specification of the opportunity identification basic data corresponding to the patent text and used as functional efficacy information features. The extracted technical features and functional efficacy information features are filled into the first two-dimensional matrix to construct the patent technology and efficacy matrix.

17. The system as claimed in claim 15, characterized in that, The non-patent literature technology and problem matrix construction submodule is specifically used for: Set up a second two-dimensional matrix with cutting-edge technology features as rows and scientific question features as columns; From the summary, keywords, and main text of the opportunity identification basic data corresponding to the article, extract the novel methods, new materials, unique structures, improved algorithms, or innovative experimental schemes of the article as features of cutting-edge technologies; Extract the core scientific challenges or technical bottlenecks of the article from the abstract, introduction, and conclusion of the opportunity identification basic data corresponding to the article, and use them as the features of the scientific problem. The extracted cutting-edge technology features and scientific problem features are filled into the second two-dimensional matrix to construct a non-patent literature technology and problem matrix.

18. The system as described in claim 15, characterized in that, The product technology and bottleneck matrix construction submodule is specifically used for: Set up a third two-dimensional matrix with the technical features of commercial products as rows and the application problems of products as columns; From the technical overview, technical roadmap, and iteration plan of the opportunity identification basic data corresponding to the product market data, mature technical solutions of the product market data are extracted as technical element features of commercial products. The application problem characteristics of the product are extracted from the manufacturer's self-report, iteration plan, and market feedback, which are the basic data for opportunity identification corresponding to the product market data. The extracted commercial product technology elements and product application problems are filled into the third two-dimensional matrix to construct the product technology and bottleneck matrix.

19. The system as claimed in claim 12, characterized in that, The blank patent technology opportunity identification submodule is specifically used for: A three-dimensional feature space of technology-efficacy-problem is constructed with technical parameters, efficacy parameters, and problem parameters as axes; the three-dimensional feature space of technology-efficacy-problem includes multiple technical units; The technical means characteristics and functional efficacy information characteristics of each pair in the patent technology and efficacy matrix of the same technical subfield, the cutting-edge technical point characteristics and scientific problem characteristics of each pair in the non-patent literature technology and problem matrix, and the commercial product technology element characteristics and application problem characteristics of each pair in the product technology and bottleneck matrix are respectively mapped into the three-dimensional feature space of technology-efficacy-problem. After scanning and determining the patent data points, literature data points, and product data points of each technical unit in the three-dimensional feature space of technology-efficacy-problem, the patent gap degree, literature problem concentration degree, and product bottleneck intensity are determined based on the patent data points, literature data points, and product data points. Based on the patent vacancy rate, the concentration of literature issues, and the product bottleneck intensity and their corresponding weights, a blank opportunity score is calculated for each technology unit. When the blank opportunity score exceeds a preset threshold and the technical feasibility assessment meets the standard, the content of the corresponding technology unit is marked as a blank patent technology opportunity. The technical unit consists of a unique technology, efficacy, and problem.

20. The system as described in claim 19, characterized in that, The formula for calculating the blank opportunity score is as follows: in, Rate the blank opportunity. For patent gaps, As a weight for patent vacancy, For the concentration of literature questions, The weight of the concentration of literature questions, For product bottleneck strength, The weighting of the bottleneck strength of the product.

21. The system as claimed in claim 12, characterized in that, The alternative patent technology opportunity identification submodule is specifically used for: From the patent technology and efficacy matrix of the same technology subfield, technical means that match the application problems in the product technology and bottleneck matrix are retrieved to generate a set of existing technical solutions; the set of existing technical solutions includes multiple existing technical solutions. In the non-patent literature technology and problem matrix, cutting-edge technology points that can solve the application problem are retrieved to generate a set of candidate alternative paths; the set of candidate alternative paths includes multiple candidate alternative path schemes. Analyze the technical path differences between existing technical solutions and corresponding candidate alternative solutions, and calculate the substitution potential index of candidate alternative solutions; When the substitution potential index is greater than the industry benchmark and there is technological substitution feasibility, the corresponding candidate substitution path scheme is marked as a substitute patent technology opportunity.

22. The system as described in claim 12, characterized in that, The evolutionary patented technology opportunity recognition submodule is specifically used for: Extract the next-generation technology direction from the iterative plan of the product technology and bottleneck matrix in the same technology subfield; The next-generation technology direction is cross-validated and reverse-mapped with the cutting-edge technology points of the non-patent literature technology and problem matrix to generate multiple iterative technologies; For each iterative technology, a technological evolution projection is performed. During the projection process, the technological growth rate, efficiency leap probability, and market demand matching degree of each iterative technology are extracted, and a technological evolution opportunity score for each iterative technology is calculated. Based on the aforementioned technology evolution opportunity score, iterative technologies that are in the technology growth stage and have the characteristics of efficiency leaps are identified and marked as evolutionary patent technology opportunities.

23. An electronic device, characterized in that, include: At least one processor and memory; The memory and processor are connected via a bus; The memory is used to store one or more programs; When the one or more programs are executed by the at least one processor, a patent technology opportunity identification method as described in any one of claims 1 to 11 is implemented.

24. A readable storage medium, characterized in that, It contains an execution program, which, when executed, implements a patent technology opportunity identification method as described in any one of claims 1 to 11.

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