Dynamic patent value method and system

Abstract

The invention relates to the technical field of patent evaluation, in particular to a dynamic patent value method and system, and the method comprises the following steps: building a patent value evaluation basic condition, carrying out the standardization processing of data through the analysis of the data of a newly applied patent, including the technology classification, the reference condition, the applicant information and the market feedback, and building an initial patent data set. According to the invention, real-time data of dynamic market feedback and technology development are combined, so that the timeliness and correlation of patent value evaluation are remarkably improved, the evaluation process is allowed to continuously adapt to the latest market and technology changes, and the evaluation result can truly reflect the current value of the patent; time sequence analysis is combined with macroeconomic data and an industry development trend, so that evaluation is not only based on historical data, but also potential market change and technical evolution in the future are predicted, deep insight in patent financial value is provided, artificial scoring is fused, comprehensiveness and multi-dimensional judgment of evaluation are optimized, and accuracy and efficiency of decision making are improved.

Description

Technical Field

[0001] The present invention relates to the field of patent evaluation technology, and in particular to a dynamic patent value method and system. Background Art

[0002] The field of patent valuation technology involves evaluating the value and impact of patents, usually based on the patent's technical content, market potential, legal status, and commercial application scope. This field uses a variety of methods to determine the financial value of patents and their potential impact on existing markets and future technological developments. During the valuation process, the legal status of the patent is considered, such as whether the patent has been granted, the geographical scope of the patent application, and the validity period of the patent. In addition, the patent's technological advancement and degree of innovation are evaluated, including novelty and non-obviousness in the relevant technical field.

[0003] Among them, the dynamic patent value method is a systematic method for estimating the economic value of a patent. It determines the value of a patent by analyzing the legal status, market application, technological advancement and its relationship with market dynamics. Its main purpose is to provide patent right holders with a scientific basis for value judgment, helping to more accurately grasp the value and commercial potential of patents when licensing, selling or using them as a basis for investment decisions. In addition, dynamic evaluation can also assist enterprises or individuals to more effectively utilize their patent assets when conducting R&D investment and market strategy planning.

[0004] The main shortcomings of existing technologies are their static evaluation model and their delayed response to market and technological changes. They usually rely on data at fixed time points and lack dynamic updates, which results in the inability of evaluation results to accurately capture immediate changes in the market and technology, affecting the effectiveness and practicality of the evaluation. For example, if a new technological breakthrough or legal policy change suddenly occurs in the market, traditional methods cannot quickly adjust the evaluation model to reflect the change, resulting in the value of patent assets being misassessed. In addition, existing technologies fail to systematically integrate macroeconomic factors and industry trend analysis, lack the necessary foresight when formulating long-term patent strategies, and are difficult to predict and respond to rapid changes in the industry, reducing the competitiveness of enterprises in the market. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a dynamic patent value method and system.

[0006] In order to achieve the above-mentioned purpose, the present invention adopts the following technical solution: a dynamic patent value method, comprising the following steps: S1: Establish the basic conditions for patent value assessment by analyzing the newly applied patent data, including technology classification, citation status, applicant information and market feedback, standardize the data, and build an initial patent data set; S2: Based on the initial patent data set, perform patent technology description analysis, extract key terms and technical innovations, calculate the innovation index of each technology, and generate technical depth and innovation evaluation results; S3: Based on the technical depth and innovation evaluation results, determine the position of the patent in the corresponding technology network, evaluate the market application potential and technological advancement of the patent, and generate a comprehensive evaluation result of the patent's influence; S4: Based on the comprehensive evaluation results of the patent influence, combined with market feedback and the speed of technological development, the patent competitiveness is updated in real time, synchronized with market and technological development, and the patent competitiveness analysis results are dynamically updated; S5: Based on the dynamically updated patent competitiveness analysis results, combined with macroeconomic data and industry development trends, conduct time series analysis to evaluate the future impact on patent value and generate potential evaluation data for patent value; S6: Based on the potential evaluation data of the patent value, draw a patent value decay curve, analyze the time value decay trend of the patent, and combine manual scoring to obtain a dynamic patent value comprehensive evaluation result.

[0007] As a further solution of the present invention, the initial patent data set includes patent technology categories, applicant identity information, number of cited documents and initial market response data, the technical depth and innovation evaluation results include technical innovation scores, key technical vocabulary extraction records and innovation feature description records, the patent influence comprehensive evaluation results include market potential scores and technological advancement ratings, the dynamically updated patent competitiveness analysis results include competitiveness indexes and market feedback analysis results, the patent value potential evaluation data include macroeconomic impact analysis results, industry trend forecast records and time series evaluation indicators, and the dynamic patent value comprehensive evaluation results include value decay curves, time value decay indicators and manual scoring results.

[0008] As a further solution of the present invention, the basic conditions for patent value assessment are established by analyzing the newly applied patent data, including technology classification, citation status, applicant information and market feedback, standardizing the data, and constructing the initial patent data set. The specific steps are as follows: S101: Collect newly applied patent data, label the technology classification data, count the number of citations, collect and analyze the applicant information, perform preliminary rating of market feedback, and generate a classified patent data set; S102: Based on the classified patent dataset, unify the data format, adjust the data coding to ensure the compatibility of the classified data, perform verification checks on all data categories to confirm the data accuracy, and obtain a standardized patent dataset; S103: Based on the standardized patent data set, integrate data items, set data access and query interfaces, and obtain an initial patent data set.

[0009] As a further solution of the present invention, based on the initial patent data set, the specific steps of performing patent technology description analysis, extracting key terms and technical innovations, calculating the innovation index of each technology, and generating technology depth and innovation evaluation results are as follows: S201: Based on the initial patent data set, perform patent technology description content screening, extract key terms, annotate the text with key terms, perform labeling processing on the graphic data, and obtain extracted terms and labeled graphic results; S202: Based on the extracted terms and labeled graphic results, identify and record the innovation points of each technology, classify and sort the innovation points according to the technical characteristics and application scenarios, and obtain a technical innovation point index; S203: Based on the technical innovation index, the innovation index is calculated for each technology through the frequency of occurrence of key terms and the impact rating of the innovation points to generate technical depth and innovation evaluation results.

[0010] As a further embodiment of the present invention, the innovation index is calculated according to the formula: ; Calculate, where Represents the frequency of a key term appearing in a specific technical document. represents the inverse document frequency, Represents the impact rating of the technological innovation point.

[0011] As a further solution of the present invention, according to the technical depth and innovation evaluation results, the position of the patent in the corresponding technology network is determined, the market application potential and technological advancement of the patent are evaluated, and the specific steps of generating the comprehensive evaluation results of the patent influence are as follows: S301: Based on the technical depth and innovation evaluation results, analyze the correlation between the patent and the nodes in the technology network, identify the directly connected technology nodes, perform positioning analysis, calibrate the position of the patent in the technology network, and obtain the patent technology network position positioning result; S302: Based on the network location positioning result of the patented technology, analyze the market demand data, compare the market performance of similar technology products, perform market potential assessment, and generate quantitative assessment results of market application potential; S303: Based on the quantitative evaluation results of the market application potential, analyze the matching degree between the technical characteristics and the current market industry standards, determine the advancement of the technology, and generate a comprehensive evaluation result of the patent influence.

[0012] As a further solution of the present invention, based on the comprehensive evaluation results of the patent influence, combined with market feedback and the speed of technological development, the patent competitiveness is updated in real time, synchronized with market and technological development, and the specific steps for obtaining the dynamically updated patent competitiveness analysis results are: S401: Based on the comprehensive evaluation results of the patent influence, market dynamics tracking is performed, market feedback data is collected and analyzed in real time, and the monitoring frequency of market demand changes is adjusted to obtain real-time tracking results of market dynamics; S402: Based on the real-time tracking results of the market dynamics, monitor the speed of technological development, analyze the update cycle of related technology fields, compare with the progress of patented technologies, and generate a synchronous analysis result of technological progress; S403: Based on the synchronous analysis results of the technological progress, update the competitiveness evaluation of the patent, match the latest information of the market and technology, and generate dynamically updated patent competitiveness analysis results.

[0013] As a further solution of the present invention, according to the dynamically updated patent competitiveness analysis results, combined with macroeconomic data and industry development trends, time series analysis is performed to evaluate the future impact on patent value. The specific steps for generating patent value potential evaluation data are as follows: S501: Based on the dynamically updated patent competitiveness analysis results, current macroeconomic indicators are collected and data is imported through a real-time data interface to obtain a macroeconomic data set; S502: Based on the macroeconomic data set, the industry investment flow and technology innovation speed data are integrated to divide and compare the development trends of different industries, conduct industry trend time series analysis, and generate industry development trend time series analysis results; S503: Based on the time series analysis results of the industry development trend and in combination with the patent competitiveness data, an assessment of the future impact of the patent value is conducted, the potential value of the patent is predicted, and potential assessment data of the patent value is generated.

[0014] As a further solution of the present invention, based on the potential evaluation data of the patent value, the patent value decay curve is drawn, the time value decay trend of the patent is analyzed, and the specific steps of obtaining the dynamic patent value comprehensive evaluation result in combination with manual scoring are as follows: S601: Based on the patent value potential evaluation data, determine the key data points of the patent value changing over time, calibrate the key data points by time series marking, and construct and output a patent value decay curve chart; S602: Based on the patent value decay curve, identify and analyze the decreasing trend of the patent value over time, detect key decay nodes, record the value index at each time point, and generate patent time value decay trend analysis results; S603: Based on the analysis results of the patent time value decay trend and combined with manual scoring by industry experts, the evaluation model is adjusted to match market insights to generate a dynamic patent value comprehensive evaluation result.

[0015] Dynamic patent value system, including: The data preparation module collects newly applied patent data, processes the data, unifies the data format, adjusts the data coding, checks and confirms the data accuracy, integrates the data items to set the data access and query interface, and obtains the initial patent data set; The technical analysis module, based on the initial patent data set, performs content screening of patent technical descriptions, extracts key terms, identifies and records the innovative points of each technology, classifies and organizes the innovative points, calculates the innovation index through the frequency of occurrence of key terms and the impact rating of the innovative points, and generates technical depth and innovation evaluation results; The market potential module analyzes the correlation between patents and nodes in the technology network based on the technical depth and innovation evaluation results, compares the market performance of similar technology products, performs market potential evaluation, analyzes the matching degree between technical characteristics and current market industry standards, and generates comprehensive evaluation results of patent influence; Based on the comprehensive evaluation results of the patent influence, the technology progress module tracks market dynamics, collects and analyzes market feedback data in real time, analyzes the update cycle of related technology fields, compares it with the patent technology progress, and generates technology progress synchronization analysis results; The macro analysis module updates the competitiveness assessment of patents based on the synchronous analysis results of the technological progress, matches the latest market and technological information, and synchronously collects current macroeconomic indicators to obtain a macroeconomic data set; The trend forecasting module integrates industry investment flow and technology innovation speed data based on the macroeconomic data set, conducts industry trend time series analysis, predicts the potential value of patents, and generates potential evaluation data of patent value; The value assessment module is based on the potential assessment data of the patent value, marks the key data points of the patent value changing over time, identifies and analyzes the downward trend of the patent value over time, and combines manual scoring to generate a dynamic patent value comprehensive assessment result.

[0016] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, by combining dynamic market feedback and real-time data of technological development, the timeliness and relevance of patent value assessment are significantly improved, allowing the assessment process to continuously adapt to the latest market and technological changes, ensuring that the assessment results can truly reflect the current value of the patent. Time series analysis is combined with macroeconomic data and industry development trends, so that the assessment is not only based on historical data, but also predicts potential future market changes and technological evolution, providing in-depth insights into the financial value of patents, integrating manual scoring, optimizing the comprehensiveness and multi-dimensional judgment of the assessment, and improving the accuracy and efficiency of decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of the steps of the present invention; Figure 2 is a flow chart of the steps of S1 of the present invention; Figure 3 is a flow chart of the steps of S2 of the present invention; Figure 4 is a flow chart of the steps of S3 of the present invention; Figure 5 is a flow chart of the steps of S4 of the present invention; Figure 6 is a flow chart of the steps of S5 of the present invention; Figure 7 is a flow chart of the steps of S6 of the present invention; Figure 8 It is a system module diagram of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0019] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0020] See also Figure 1 , dynamic patent value method, including the following steps: S1: Establish the basic conditions for patent value assessment by analyzing the newly applied patent data, including technology classification, citation status, applicant information and market feedback, standardize the data, and build an initial patent data set; S2: Based on the initial patent data set, perform patent technology description analysis, extract key terms and technical innovations, calculate the innovation index of each technology, and generate technical depth and innovation evaluation results; S3: Based on the results of the technical depth and innovation evaluation, determine the position of the patent in the corresponding technology network, evaluate the market application potential and technological advancement of the patent, and generate a comprehensive evaluation result of the patent's influence; S4: Based on the comprehensive evaluation results of patent influence, combined with market feedback and the speed of technological development, the patent competitiveness is updated in real time, synchronized with market and technological development, and the patent competitiveness analysis results are dynamically updated; S5: Based on the dynamically updated patent competitiveness analysis results, combined with macroeconomic data and industry development trends, conduct time series analysis to assess the future impact on patent value and generate potential patent value assessment data; S6: Based on the potential evaluation data of patent value, draw the patent value decay curve, analyze the time value decay trend of the patent, and combine with manual scoring to obtain the dynamic patent value comprehensive evaluation results.

[0021] The initial patent data set includes patent technology categories, applicant identity information, number of cited documents and initial market response data. The technical depth and innovation evaluation results include technical innovation scores, key technical vocabulary extraction records and innovation feature description records. The comprehensive evaluation results of patent influence include market potential scores and technological advancement ratings. The dynamically updated patent competitiveness analysis results include competitiveness indexes and market feedback analysis results. The potential evaluation data of patent value include macroeconomic impact analysis results, industry trend forecast records and time series evaluation indicators. The dynamic patent value comprehensive evaluation results include value decay curves, time value decay indicators and manual scoring results.

[0022] See also Figure 2 , the specific steps of S1 are: S101: Collect newly applied patent data, label the technology classification data, count the number of citations, collect and analyze the applicant information, perform preliminary rating of market feedback, and generate a classified patent data set; When collecting new patent application data and labeling technology classification data, first screen patent applications that meet the preset technology categories, such as electronics, machinery or biotechnology, and associate each patent data with the corresponding technology category to ensure that the technical attributes of each data entry are clearly recorded. Perform more detailed labeling on patents within each technology category, such as further distinguishing between communication technology and computing technology in electronic technology. Use natural language processing (NLP) tools to parse patent descriptions and statements for accurate classification and labeling. When performing citation statistics, count the frequency of citations for each patent to determine the influence and relevance of the patent. Patents with high citation counts are more likely to be cited. Patents with high impact will be marked as high-impact patents in the dataset. When collecting and analyzing applicant information, the applicant's identity information, historical application records, etc. are collected. Through association analysis methods, such as association rule mining, the relationship between the application patterns of different applicants and the patent quality is analyzed to help identify the applicant's patent application behavior and quality trends. A preliminary rating is conducted on market feedback data, such as the commercial application of patents, market demand survey results, etc. The rating standards are set according to the actual application benefits and market acceptance of the patents. The market data is combined with the patent data to form a comprehensive market feedback rating and generate a classified patent dataset.

[0023] S102: Based on the classified patent dataset, unify the data format, adjust the data coding to ensure the compatibility of the classified data, perform verification checks on all data categories to confirm the data accuracy, and obtain a standardized patent dataset; When unifying the data format based on the classified patent dataset, first ensure that all data entries follow a unified data structure and encoding system, such as XML or JSON format. By writing data conversion scripts, convert patent data from different sources and formats into a unified format. During the conversion process, pay special attention to special characters and encoding differences in the data, such as the conversion between ASCII and UTF-8 encoding, to ensure data consistency and readability. Adjust data encoding to ensure the compatibility of classified data, including standardizing specific fields such as dates and country codes to adapt to the data requirements of different systems and applications. Perform validation checks on all data categories to confirm data accuracy. By setting automated validation rules, such as field type checks, data range validation, and necessity validation, each record in the dataset is strictly checked to ensure that the data is not only in a unified format, but also conforms to logic and business rules, so as to obtain a standardized patent dataset.

[0024] S103: Based on the standardized patent data set, integrate data items, set data access and query interfaces, and obtain the initial patent data set; Based on the standardized patent data set, when integrating data items, it is necessary to integrate the various fields in the data set, such as patent number, application date, and technical field label, to create a more comprehensive data view. For example, similar data fields can be merged through data fusion technology to eliminate duplicate records to enhance data integrity and availability. Data access and query interfaces are set to provide users with a unified data access point. The interface design includes RESTful API or GraphQL API. The interface allows users to query patent information according to their needs, such as filtering according to application date or technical field. The implementation of the interface ensures the flexibility and security of data access. The authentication and authorization mechanism is used to protect the data from unauthorized access, obtain the initial patent data set, and provide data resources for further analysis and application to support various business needs such as patent analysis, market forecasting, and strategy formulation.

[0025] See also Figure 3 , the specific steps of S2 are: S201: Based on the initial patent data set, perform patent technology description content screening, extract key terms, annotate the text with key terms, perform labeling processing on the graphic data, and obtain the extracted terms and labeled graphic results; Based on the initial patent data set, when performing patent technology description content screening, first scan the patent document set to identify and extract sentences containing technical terms. Through the preset technical keyword list, the keywords cover the common technical terms of each patent classification, such as "semiconductor", "bioengineering", "quantum computing", etc. After extracting the key terms, the terms are annotated and classified in detail according to the technical field and application background of the terms. When performing labeling processing on graphic materials, the graphics and image materials in the patents are analyzed to identify the key elements in the figures, such as components, devices, etc., and associate the graphic materials with relevant technical terms to ensure that the label of each figure closely corresponds to its content, and obtain the results of extracted terms and labeled graphics, which include complete technical descriptions and graphic data.

[0026] S202: Based on the extracted terms and labeled graphic results, identify and record the innovation points of each technology, classify and sort the innovation points according to the technical characteristics and application scenarios, and obtain an index of technical innovation points; Based on the extracted terms and labeled graphic results, when identifying and recording the innovative points of each technology, the detailed content of each patent is reviewed in depth, with special attention paid to the improvement or breakthrough of each technology compared with the existing technology. By comparing and analyzing the key terms in the patent description with the known technical standards, the specific content of the innovative points is clarified, such as the use of new materials, methods to improve efficiency or new application scenarios. According to the classification of technical characteristics and application scenarios, each technology is carefully classified according to its application fields such as medical, environmental protection, communications, etc., and the innovative points are classified and sorted to obtain an index of technical innovation points, which provides a tool for quick access to various technical innovation points and helps to evaluate the market potential and technical value of patents.

[0027] S203: Based on the technical innovation index, the innovation index is calculated for each technology through the frequency of occurrence of key terms and the impact rating of the innovation points, generating the technical depth and innovation evaluation results; Innovation index, according to the formula, ; Calculate, where Represents the frequency of a key term in a specific technical document, representing the local importance of the term in the document. stands for inverse document frequency, which measures the general importance of a term, Represents the impact rating of the technological innovation point.

[0028] Indicates the frequency of a key term appearing in a specific technical document. If the key term "artificial intelligence" appears 15 times in a document, then .

[0029] represents the inverse document frequency, which is used to measure the general importance of a term. If the total number of documents is 1000 and the number of documents containing the term "artificial intelligence" is 100, then .

[0030] Indicates the impact rating of a technology's innovation point. A certain technology was rated 3.5 (on a 5-point scale, the impact increases from 1 to 5, which means the innovation is becoming more and more outstanding).

[0031] set up , , .

[0032] First calculate : ; calculate : ; Compute products under square roots: ; Calculate the denominator: ; Final calculation : ; The results show that the given technology entry obtained a comprehensive innovation index of 0.86 in the technology innovation evaluation. This value reflects the combined effect of the importance of key terms and the influence of technological innovation points in the overall evaluation. A higher value indicates that the technology has stronger innovation and market influence.

[0033] See also Figure 4 , the specific steps of S3 are: S301: Based on the results of technology depth and innovation evaluation, analyze the correlation between the patent and the nodes in the technology network, identify the directly connected technology nodes, perform positioning analysis, calibrate the position of the patent in the technology network, and obtain the patent technology network position positioning result; Based on the results of technology depth and innovation evaluation, when analyzing the correlation between patents and nodes in the technology network, we first visualize the connection between patent technology and existing technology nodes through technology network map analysis, identify directly connected technology nodes related to the patent, evaluate the influence and importance of each technology node, record the connection strength between each node, and perform positioning analysis. Combined with the evaluation results, we determine the specific position of each patent in the technology network, and use hierarchical clustering to group technology nodes according to similarity, so that we can accurately calibrate the position of each patent in the technology network, and obtain the patent technology network position positioning results, which shows the status of the patent in the technology network relative to other technologies and provides basic data for subsequent market demand analysis and potential evaluation.

[0034] S302: Based on the network location positioning results of the patented technology, analyze the market demand data, compare the market performance of similar technology products, perform market potential assessment, and generate quantitative assessment results of market application potential; When analyzing market demand data based on the results of patent technology network location positioning, the team first collects relevant market demand data, including consumer preferences, market performance and sales data of competing products, uses market research reports to compare the market performance of similar technology products, analyzes their sales, market share and user feedback, and establishes a market performance database. Through data mining technology, key market trends are identified, and the competitive advantages of different technology products in the same market environment are evaluated. Combined with the results of patent technology network positioning, multi-dimensional data analysis methods are used to determine the market potential of various technologies, perform market potential assessments, and generate quantitative assessment results of market application potential, which provides a quantitative basis for subsequent technology promotion and commercialization decisions, ensuring that companies can make adjustments based on market dynamics.

[0035] S303: Based on the quantitative evaluation results of market application potential, analyze the matching degree between technical characteristics and current market industry standards, determine the advancement of technology, and generate comprehensive evaluation results of patent influence; Based on the quantitative evaluation results of market application potential, when analyzing the matching degree between technical characteristics and current market industry standards, we conduct a detailed review of various technical characteristics, clarify their performance indicators, applicable scope and technical parameters, collect current market industry standard data, and establish a standard database. Through comparative analysis, we evaluate the differences between technical characteristics and industry standards, test the advancement of technologies item by item, determine which technologies meet or exceed industry standards, and determine which technologies demonstrate their advancement in the industry. We generate comprehensive evaluation results of patent influence, which provide a basis for evaluating the market adaptability and potential value of technologies and help companies make more scientific decisions on technology research and development and market strategies.

[0036] See also Figure 5 , the specific steps of S4 are: S401: Based on the comprehensive evaluation results of patent influence, market dynamics tracking is carried out, market feedback data is collected and analyzed in real time, the monitoring frequency of market demand changes is adjusted, and real-time tracking results of market dynamics are obtained; Based on the comprehensive evaluation results of patent influence, when tracking market dynamics, a market feedback data collection mechanism is established to monitor the sales data, user evaluations and market trends of competing products in real time, organize feedback data, and set the monitoring frequency to weekly in order to promptly reflect changes in market demand. The collected data is cleaned and organized, and irrelevant or noise data is eliminated to ensure the validity of the analysis results. Dynamic classification is carried out for different products and market segments, and combined with time series data of market feedback, real-time tracking results of market dynamics are formed, which provides an important basis for subsequent technology development monitoring and market strategy adjustments.

[0037] S402: Based on the real-time tracking results of market dynamics, monitor the speed of technological development, analyze the update cycle of related technology fields, compare with the progress of patented technology, and generate synchronous analysis results of technological progress; Based on the real-time tracking results of market dynamics and when monitoring the speed of technological development, we first classify the technologies involved in market feedback, collect update cycle information in various technical fields, build a technology update database, analyze the market performance and update frequency of directly related technologies, use time series analysis methods to compare the progress of these technologies with the progress of patented technologies, set key performance indicators to quantify the speed of technological development, use difference analysis methods to evaluate the synchronization between technological development and patent progress, and generate technology progress synchronization analysis results by comparing the technology update cycle with changes in market demand. This result provides an important reference for further competitiveness evaluation.

[0038] S403: Based on the results of synchronous analysis of technological progress, update the competitiveness assessment of patents, match the latest information on the market and technology, and generate dynamically updated patent competitiveness analysis results; Based on the results of synchronous analysis of technological progress, when updating the competitiveness assessment of patents, the latest data on technological progress and market dynamics are extracted, the technical characteristics and performance indicators of patented technologies are compared with those of similar products on the market, and dynamic assessments are conducted to reflect the importance of market and technical information, analyze the degree of match between the technical characteristics of patents and current industry standards, and combine market feedback to evaluate the relative position of patented technologies in the industry. Dynamically updated patent competitiveness analysis results are generated, which will guide subsequent market strategies and technology optimization directions.

[0039] See also Figure 6 , the specific steps of S5 are: S501: Based on the dynamically updated patent competitiveness analysis results, collect current macroeconomic indicators, import data through the real-time data interface, and obtain a macroeconomic data set; Import real-time macroeconomic data. The data comes from the economic data API interface, which provides real-time data on GDP growth rates and inflation rates of various countries. The data is requested through the API call script. The obtained data includes timestamps and corresponding economic indicator values. The received data format is JSON. The timestamp in the data ensures the timeliness and accuracy of the data. The received data is preliminarily cleaned to remove any null values ​​or format errors in the data to ensure data quality and provide an accurate input source for subsequent analysis. The cleaned data is then stored in a relational database. The data table in the database is pre-designed with corresponding fields, such as date, GDP growth rate, inflation rate, etc., to facilitate subsequent query and analysis and obtain a macroeconomic data set.

[0040] S502: Based on the macroeconomic data set, integrate the industry investment flow and technology innovation speed data, divide and compare the development trends of different industries, conduct industry trend time series analysis, and generate industry development trend time series analysis results; Based on the collected and integrated macroeconomic data sets, the industry investment flow and technological innovation speed data are integrated. The data sets are merged through SQL queries, and the macroeconomic indicators are associated with industry data. Economic impact factors, such as investment amount and frequency of innovation activities, are marked for each industry. Industry data are obtained through annual reports and market surveys of various industries. Time series analysis is performed on the data. The ts model in STATA or R is used to set the model. The model includes seasonal adjustment and trend analysis. The development trends of various industries are identified through analysis and visualized. The charts show the performance of various industries under different economic environments, as well as the impact of technological innovation on industry development, and generate time series analysis results of industry development trends.

[0041] S503: Based on the results of the time series analysis of industry development trends and combined with patent competitiveness data, conduct an assessment of the future impact of patent value, predict the potential value of patents, and generate potential assessment data for patent value; The results of the time series analysis of industry development trends are combined with patent competitiveness data. The patent competitiveness data comes from patent databases and market analysis reports, including indicators such as the number of patent applications, authorization success rate and citation frequency. The data is statistically analyzed and a multiple regression analysis model is used to estimate the future influence of patents. The model incorporates industry development trends as explanatory variables, as well as historical performance data of patents. The potential economic value of each patent is analyzed through the model. The model output includes predicted values ​​and confidence intervals, which evaluate the market impact and value conversion potential that each patent may bring in the future, and generate potential evaluation data for patent value.

[0042] See also Figure 7 , the specific steps of S6 are: S601: Based on the potential evaluation data of patent value, determine the key data points of patent value changing over time, calibrate the key data points through time series marking, and construct and output a patent value decay curve chart; To determine the key data points of patent value changes over time, first use the patent value potential evaluation data set, apply the time series analysis method to determine the significant points of data fluctuations, analyze the value of each time point in the data set, use the difference and rolling average methods to identify trend changes worthy of attention, select significant change points as key data points, and mark important turning points or changes in patent value. For each key point, record its timestamp and corresponding patent value. Data points are automatically marked to ensure that the selection of each key point is both accurate and repeatable. Then use graphical tools, such as Python's Matplotlib library, to mark the key points on the patent value decay curve. Each marked point in the figure clearly shows the time and value, and construct and output the patent value decay curve.

[0043] S602: Based on the patent value decay curve, identify and analyze the decreasing trend of patent value over time, detect key decay nodes, record the value index at each time point, and generate patent time value decay trend analysis results; Based on the patent value decay curve, identify the downward trend of patent value over time. First, read the key data points from the decay curve, identify the trend of key data points through statistical analysis, and quantitatively analyze the rate of decline of patent value by calculating the slope and intercept of the trend line. Record each key decay node, including the timestamp of the node and the corresponding patent value. Use data analysis software such as Excel or R to perform node analysis, ensure that the specific information of each node is recorded, including its position in the overall trend and its value impact. Record the analysis results and conclusions of each step to generate the patent time value decay trend analysis results.

[0044] S603: Based on the analysis results of the patent time value decay trend and combined with the manual scoring of industry experts, the evaluation model is adjusted to match market insights to generate dynamic patent value comprehensive evaluation results; Based on the analysis results of the patent time value decay trend and combined with manual scoring by industry experts, we first collect the scores of industry experts, which reflect the market's insights into the current and future value of patents. We collect data through expert meetings, and each expert provides a value assessment of different patents. The scores are integrated and analyzed, and statistical methods are used to calculate the mean and standard deviation of the scores. Based on the expert scoring results, we adjust the parameters of the patent value assessment model, such as weights and preference settings, to ensure that the model can more accurately reflect market conditions. We recalculate the value of the patent through the model to generate dynamic patent value comprehensive assessment results.

[0045] See also Figure 8 , dynamic patent value system, including: The data preparation module collects newly applied patent data, processes the data, unifies the data format, adjusts the data coding, checks and confirms the data accuracy, integrates the data items to set the data access and query interface, and obtains the initial patent data set; The technical analysis module is based on the initial patent data set, performs patent technology description content screening, extracts key terms, identifies and records the innovation points of each technology, classifies and organizes the innovation points, calculates the innovation index through the frequency of occurrence of key terms and the impact rating of the innovation points, and generates technical depth and innovation evaluation results; The market potential module analyzes the correlation between patents and nodes in the technology network based on the results of technology depth and innovation evaluation, compares the market performance of similar technology products, performs market potential evaluation, analyzes the matching degree between technology characteristics and current market industry standards, and generates comprehensive evaluation results of patent influence; The technology progress module tracks market dynamics based on the comprehensive evaluation results of patent influence, collects and analyzes market feedback data in real time, analyzes the update cycle of related technology fields, compares it with patent technology progress, and generates technology progress synchronization analysis results; The macro analysis module updates the competitiveness assessment of patents based on the results of synchronous analysis of technological progress, matches the latest information on the market and technology, and simultaneously collects current macroeconomic indicators to obtain a macroeconomic data set; The trend forecasting module is based on macroeconomic data sets, integrates industry investment flows and technology innovation speed data, conducts industry trend time series analysis, predicts the potential value of patents, and generates potential evaluation data for patent value; The value assessment module is based on the potential assessment data of patent value, marks the key data points of patent value changes over time, identifies and analyzes the downward trend of patent value over time, and combines manual scoring to generate dynamic patent value comprehensive assessment results.

[0046] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. Dynamic patent value method, characterized by: The following steps are involved: Establish the basic conditions for patent value assessment, standardize the data by analyzing the newly applied patent data, including technology classification, citation status, applicant information and market feedback, and build an initial patent data set; Based on the initial patent data set, perform patent technology description analysis, extract key terms and technical innovations, calculate the innovation index of each technology, and generate technical depth and innovation evaluation results; Based on the technical depth and innovation evaluation results, determine the position of the patent in the corresponding technology network, evaluate the market application potential and technological advancement of the patent, and generate a comprehensive evaluation result of the patent's influence; Based on the comprehensive evaluation results of the patent influence, combined with market feedback and the speed of technological development, the patent competitiveness is updated in real time, synchronized with market and technological development, and the patent competitiveness analysis results are dynamically updated; Based on the dynamically updated patent competitiveness analysis results, combined with macroeconomic data and industry development trends, time series analysis is conducted to assess the future impact on patent value and generate potential patent value assessment data; Based on the potential evaluation data of the patent value, a patent value decay curve is drawn, and the time value decay trend of the patent is analyzed. Combined with manual scoring, a dynamic comprehensive evaluation result of the patent value is obtained.

2. The dynamic patent value method according to claim 1, characterized in that: The initial patent data set includes patent technology categories, applicant identity information, number of cited documents and initial market response data; the technical depth and innovation evaluation results include technical innovation scores, key technical vocabulary extraction records and innovation feature description records; the patent influence comprehensive evaluation results include market potential scores and technological advancement ratings; the dynamically updated patent competitiveness analysis results include competitiveness indexes and market feedback analysis results; the patent value potential evaluation data include macroeconomic impact analysis results, industry trend forecast records and time series evaluation indicators; the dynamic patent value comprehensive evaluation results include value decay curves, time value decay indicators and manual scoring results.

3. The dynamic patent value method according to claim 1, characterized in that: The specific steps to establish the basic conditions for patent value assessment are as follows: by analyzing the newly applied patent data, including technology classification, citation status, applicant information and market feedback, standardizing the data, and constructing the initial patent data set: Collect new patent application data, label technology classification data, count citations, collect and analyze applicant information, perform preliminary ratings on market feedback, and generate classified patent data sets; Based on the classified patent dataset, the data format is unified, the data coding is adjusted to ensure the compatibility of the classified data, and verification checks are performed on all data categories to confirm the data accuracy, so as to obtain a standardized patent dataset; Based on the standardized patent data set, data items are integrated, data access and query interfaces are set, and an initial patent data set is obtained.

4. The dynamic patent value method according to claim 1, characterized in that: Based on the initial patent data set, the specific steps of performing patent technology description analysis, extracting key terms and technical innovations, calculating the innovation index of each technology, and generating technology depth and innovation evaluation results are as follows: Based on the initial patent data set, perform patent technology description content screening, extract key terms, annotate the text with key terms, perform labeling processing on the graphic data, and obtain extracted terms and labeled graphic results; Based on the extracted terms and labeled graphic results, identify and record the innovation points of each technology, classify and sort the innovation points according to the technical characteristics and application scenarios, and obtain an index of technical innovation points; Based on the technical innovation index, the innovation index is calculated for each technology through the frequency of occurrence of key terms and the impact rating of the innovation points, generating technical depth and innovation evaluation results.

5. The dynamic patent value method according to claim 4, characterized in that: The innovation index, according to the formula, ； Calculate, where Represents the frequency of a key term in the target technical document. represents the inverse document frequency, Represents the impact rating of the technological innovation point.

6. The dynamic patent value method according to claim 1, characterized in that: Based on the technical depth and innovation evaluation results, the specific steps to determine the position of the patent in the corresponding technology network, evaluate the market application potential and technological advancement of the patent, and generate the comprehensive evaluation results of the patent influence are as follows: Based on the technical depth and innovation evaluation results, analyze the correlation between the patent and the nodes in the technology network, identify the directly connected technology nodes, perform positioning analysis, calibrate the position of the patent in the technology network, and obtain the patent technology network position positioning results; Based on the network location positioning results of the patented technology, analyze market demand data, compare the market performance of similar technology products, perform market potential assessment, and generate quantitative assessment results of market application potential; Based on the quantitative evaluation results of the market application potential, the matching degree between the technical characteristics and the current market industry standards is analyzed, the advancement of the technology is determined, and a comprehensive evaluation result of the patent influence is generated.

7. The dynamic patent value method according to claim 1, characterized in that: Based on the comprehensive evaluation results of patent influence, combined with market feedback and the speed of technological development, the patent competitiveness is updated in real time, in sync with market and technological development, and the specific steps for obtaining dynamically updated patent competitiveness analysis results are as follows: Based on the comprehensive evaluation results of the patent influence, market dynamics tracking is carried out, market feedback data is collected and analyzed in real time, and the monitoring frequency of market demand changes is adjusted to obtain real-time tracking results of market dynamics; Based on the real-time tracking results of the market dynamics, monitor the speed of technological development, analyze the update cycle of related technology fields, compare with the progress of patented technologies, and generate synchronous analysis results of technological progress; Based on the synchronous analysis results of the technological progress, the competitiveness evaluation of the patent is updated, the latest information on the market and technology is matched, and dynamically updated patent competitiveness analysis results are generated.

8. The dynamic patent value method according to claim 1, characterized in that: Based on the dynamically updated patent competitiveness analysis results, combined with macroeconomic data and industry development trends, time series analysis is conducted to evaluate the future impact on patent value. The specific steps for generating potential patent value evaluation data are as follows: Based on the dynamically updated patent competitiveness analysis results, current macroeconomic indicators are collected and data is imported through a real-time data interface to obtain a macroeconomic data set; Based on the macroeconomic data set, the industry investment flow and technology innovation speed data are integrated to divide and compare the development trends of different industries, conduct industry trend time series analysis, and generate industry development trend time series analysis results; Based on the time series analysis results of the industry development trends and combined with patent competitiveness data, an assessment of the future impact of patent value is conducted, the potential value of patents is predicted, and potential assessment data of patent value is generated.

9. The dynamic patent value method according to claim 1, characterized in that: Based on the potential evaluation data of the patent value, the specific steps of drawing the patent value decay curve, analyzing the time value decay trend of the patent, and combining manual scoring to obtain the dynamic patent value comprehensive evaluation results are as follows: Based on the potential evaluation data of the patent value, determine the key data points of the patent value changing over time, calibrate the key data points by time series marking, and construct and output a patent value decay curve chart; Based on the patent value decay curve, identify and analyze the decreasing trend of patent value over time, detect key decay nodes, record the value index at each time point, and generate patent time value decay trend analysis results; Based on the analysis results of the patent time value decay trend and combined with manual scoring by industry experts, the evaluation model is adjusted to match market insights and generate dynamic patent value comprehensive evaluation results.

10. Dynamic patent value system, characterized by: According to the dynamic patent value method according to any one of claims 1 to 9, the system comprises: The data preparation module collects newly applied patent data, processes the data, unifies the data format, adjusts the data coding, checks and confirms the data accuracy, integrates the data items to set the data access and query interface, and obtains the initial patent data set; The technical analysis module, based on the initial patent data set, performs content screening of patent technical descriptions, extracts key terms, identifies and records the innovative points of each technology, classifies and organizes the innovative points, calculates the innovation index through the frequency of occurrence of key terms and the impact rating of the innovative points, and generates technical depth and innovation evaluation results; The market potential module analyzes the correlation between patents and nodes in the technology network based on the technical depth and innovation evaluation results, compares the market performance of similar technology products, performs market potential evaluation, analyzes the matching degree between technical characteristics and current market industry standards, and generates comprehensive evaluation results of patent influence; Based on the comprehensive evaluation results of the patent influence, the technology progress module tracks market dynamics, collects and analyzes market feedback data in real time, analyzes the update cycle of related technology fields, compares it with the patent technology progress, and generates technology progress synchronization analysis results; The macro analysis module updates the competitiveness assessment of patents based on the synchronous analysis results of the technological progress, matches the latest market and technological information, and synchronously collects current macroeconomic indicators to obtain a macroeconomic data set; The trend forecasting module integrates industry investment flow and technology innovation speed data based on the macroeconomic data set, conducts industry trend time series analysis, predicts the potential value of patents, and generates potential evaluation data of patent value; The value assessment module is based on the potential assessment data of the patent value, marks the key data points of the patent value changing over time, identifies and analyzes the downward trend of the patent value over time, and combines manual scoring to generate a dynamic patent value comprehensive assessment result.

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