New technology identification method and device based on science and technology information, computer equipment, storage medium and program product

Abstract

The invention provides an emerging technology identification method and device based on science and technology information, computer equipment, a storage medium and a program product, and the method comprises the steps: carrying out the technical association mining of each piece of text data in a target field science and technology information data set, and obtaining at least one technology cluster; wherein the scientific and technological information data set comprises text data corresponding to scientific and technological achievements disclosed in a target field; calculating the time novelty, innovation novelty, growth, technical influence and social influence of the technical cluster based on the description data of each text data in each technical cluster, and obtaining the emerging degree of the technical cluster based on the time novelty, innovation novelty, growth, technical influence and social influence of the technical cluster. The emerging technology identification method based on the science and technology information has the advantage of accurately identifying the technology type.

Description

Technical Field

[0001] The present invention relates to the field of data mining technology, and in particular to a method, device, computer equipment, storage medium and program product for identifying emerging technologies based on scientific and technological information. Background Art

[0002] Emerging describes the trend and direction of technological change. Exploring emerging tobacco technologies is conducive to timely and accurate capture and identification of technological development opportunities, deployment and occupation of technological commanding heights, and providing key technology research and development support and guidance for the development of the tobacco industry. Key core technology needs and technology foresight are extremely important components in the process of a country or industry formulating medium- and long-term science and technology development plans, and play a strategic decision-making support function.

[0003] CN116595192A proposes a method, device, electronic device and readable storage medium for acquiring emerging scientific and technological information. The method uses text data corresponding to the scientific and technological achievements disclosed in the target field as source data, extracts the SAO structure in the bibliographic information and performs semantic analysis on the bibliographic information, determines the association between knowledge nodes and each knowledge node, and comprehensively represents the degree of emergence of knowledge nodes in the target field with five indicators, namely, novelty, attention, growth, intersection and value of knowledge nodes, to achieve a comprehensive analysis of emerging scientific and technological information, improve the limitations of the analysis of the degree of emergence in a single direction, and acquires emerging scientific and technological information by constructing a tree structure of emerging scientific and technological information. The tree structure of emerging scientific and technological information can intuitively reflect the branch relationship between each knowledge node, achieve accurate expression of emerging scientific and technological information, and effectively improve the efficiency of acquiring emerging scientific and technological information and the accuracy of the results of acquiring emerging scientific and technological information.

[0004] However, the current technical information in the tobacco field is scattered and complex, and multiple technical fields are cross-integrated. It is difficult to deeply understand the content and grasp the technological development trend by relying solely on the information in the catalog of scientific and technological literature. Therefore, using text data mining technology to discover and analyze emerging technologies in the tobacco field has important research value and application prospects. By mining patent and paper text data in the tobacco field, the latest research results, technological trends and innovations in tobacco planting, tobacco product research and development, tobacco processing, etc. can be obtained, thereby providing scientific basis and decision-making support for the technological development of the tobacco industry.

[0005] In order to solve the above problems, people have been seeking an ideal technical solution. Summary of the invention

[0006] Based on this, it is necessary to provide an emerging technology identification method, device, computer equipment, storage medium and program product based on scientific and technological information to address the above technical issues.

[0007] In order to achieve the above object, the present invention provides a method for identifying emerging technologies based on scientific and technological information in a first aspect, comprising the following steps: Performing technical association mining on each text data in the target field science and technology information data set to obtain at least one technology cluster; wherein the science and technology information data set includes text data corresponding to the scientific and technological achievements disclosed in the target field; Calculate the temporal novelty, innovative novelty, growth, technological impact, and social impact of the technology cluster based on the bibliographic data of each text data in each technology cluster; Among them, the time novelty is used to characterize the average publication time of the scientific and technological achievements corresponding to the technology cluster; the innovation novelty is used to characterize the total number of citations of the scientific and technological achievements corresponding to the technology cluster; the growth is used to characterize the average growth rate of the scientific and technological achievements corresponding to the technology cluster; the technological impact is used to characterize the technology citations of the scientific and technological achievements corresponding to the technology cluster; the social impact is used to characterize the total number of R&D personnel of the scientific and technological achievements corresponding to the technology cluster; The degree of emergence of the technology cluster is obtained based on the temporal novelty, innovative novelty, growth, technological impact and social impact of the technology cluster.

[0008] In an optional embodiment of the first aspect, the temporal novelty, innovative novelty, growth, technological impact, and social impact of each technology cluster are calculated based on the bibliographic data of each text data in the target field scientific and technological information dataset, including: Based on the publication time and number of the published texts of the text data in the technology cluster, obtaining the temporal novelty of the technology cluster; Based on the number of texts cited by the text data in the technology cluster, the innovation novelty of the technology cluster is obtained; Based on the amount of text in the text data of the technology cluster in different time periods, obtaining the growth of the technology cluster; Based on the number of citations of text data in the technology cluster and the number of citations of all patents authorized in the same year, the technical impact of the technology cluster is obtained; Based on the amount of text data in the technology cluster and the corresponding number of R&D personnel, the social influence of the technology cluster is obtained.

[0009] In an optional embodiment of the first aspect, the scientific and technological achievements disclosed in the target field are patents; The calculation of the temporal novelty, innovative novelty, growth, technological impact, and social impact of the technology cluster based on the bibliographic data of each text data in each technology cluster includes: Based on at least one patent text in each technology cluster, obtain the temporal novelty, innovative novelty, growth, technological impact, and social impact of the technology cluster; The method of obtaining the emerging degree of the technology cluster based on the temporal novelty, innovative novelty, growth, technological impact, and social impact of the technology cluster includes: According to the first preset weight allocation rule, the temporal novelty, innovative novelty, growth, technological impact, and social impact of the patent are weighted and integrated to obtain the emerging score of the technology cluster.

[0010] Furthermore, technical association mining is performed on each text data in the target field science and technology information data set to obtain at least one technology cluster, including: The CRF model is used to extract SAO triples from the patent abstract text, and SAO is screened based on the patent keywords generated by the large language model to obtain the SAO triples of each patent. The SAO triples corresponding to each patent are semantically represented based on the Bert model, and synonyms of SAO triples are merged based on KMeans clustering; A technology association network is constructed based on the association relationship of SAO triplets, and technology clusters are divided based on the graph theory community detection method.

[0011] In another optional embodiment of the first aspect, the scientific and technological achievements disclosed in the target field are papers; The calculation of the temporal novelty, innovative novelty, growth, technological impact, and social impact of the technology cluster based on the bibliographic data of each text data in each technology cluster includes: Based on at least one paper text in each technology cluster, obtain the temporal novelty, growth, and social impact of the technology cluster; The method of obtaining the emerging degree of the technology cluster based on the temporal novelty, innovative novelty, growth, technological impact, and social impact of the technology cluster includes: According to the second preset weight allocation rule, the temporal novelty, growth, and social impact of the paper are weighted and integrated to obtain the emerging score of the technology cluster.

[0012] Furthermore, technical association mining is performed on each text data in the target field science and technology information data set to obtain at least one technology cluster, including: The SAO triples of the paper text are extracted by using text mining methods, and SAO screening is performed based on the paper keywords to obtain the SAO triples of each paper; the paper keywords are the paper keywords in the field paper keyword vocabulary, and the field paper keyword vocabulary is constructed by extracting the paper keywords in the paper text bibliography and extracting the paper keywords in the paper abstract; The SAO triples corresponding to each patent are semantically represented based on the Bert model, and the synonyms of SAO triples are merged based on KMeans clustering; A technology association network is constructed based on the association relationship of SAO triplets, and technology clusters are divided based on the graph theory community detection method.

[0013] In order to achieve the above-mentioned object, the second aspect of the present invention provides an emerging technology identification device based on scientific and technological information, comprising: A technology cluster acquisition module is used to perform technology association mining on each text data in the target field science and technology information data set to obtain at least one technology cluster; wherein the science and technology information data set includes text data corresponding to the scientific and technological achievements disclosed in the target field; A technology cluster index acquisition module is used to calculate the temporal novelty, innovative novelty, growth, technological impact, and social impact of the technology cluster based on the bibliographic data of each text data in each technology cluster; wherein the temporal novelty is used to characterize the average disclosure time of the scientific and technological achievements corresponding to the technology cluster; the innovative novelty is used to characterize the total number of citations of the scientific and technological achievements corresponding to the technology cluster; the growth is used to characterize the average growth rate of the scientific and technological achievements corresponding to the technology cluster; the technological impact is used to characterize the number of technology citations of the scientific and technological achievements corresponding to the technology cluster; and the social impact is used to characterize the total number of R&D personnel of the scientific and technological achievements corresponding to the technology cluster; The module for acquiring the degree of technological emergence acquires the degree of emergence of the technology cluster based on the temporal novelty, innovative novelty, growth, technological impact, and social impact of the technology cluster.

[0014] In order to achieve the above-mentioned purpose, the third aspect of the present invention provides a computer device, including a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; the memory is used to store computer programs; the processor is used to implement the emerging technology identification method based on scientific and technological information as described in the first aspect when executing the program stored in the memory.

[0015] In order to achieve the above-mentioned purpose, the fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for identifying emerging technologies based on scientific and technological information as described in the first aspect is implemented.

[0016] In order to achieve the above-mentioned purpose, the fifth aspect of the present invention provides a computer program product, including a computer program, which, when executed by a processor, implements the emerging technology identification method based on scientific and technological information as described in the first aspect.

[0017] The beneficial effects of the present invention are: The present invention uses the improved SAO method to deeply analyze text data, dig out the intricate connections between technologies, and provide a macro and micro perspective for scientific and technological development; specifically, in the data preprocessing stage, emerging technologies such as synonymous merging, semantic association analysis, and named entity recognition are used to ensure high accuracy and depth of information extraction; at the same time, a large language model is used to generate patent keywords, which further enhances the professionalism and accuracy of the SAO method; Based on the connection between technologies, at least one technology cluster is obtained, and a corresponding indicator system is designed for emerging technologies - temporal novelty, innovation novelty, growth, technological impact, and social impact. Then, based on the text data in each technology cluster, each technical indicator of the technology cluster is calculated, and based on the various technical indicators, the degree of emergence of the technology cluster is obtained. Finally, the key technical points and innovation points are accurately identified, thereby providing a scientific basis and decision-making support for the technological development of the tobacco industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a flowchart of the emerging technology identification method based on scientific and technological information according to Embodiment 1 of the present invention; Figure 2 It is a schematic diagram of the present invention for mining technical associations of various text data in a target field scientific and technological information data set.

[0019] Figure 3 It is a structural schematic diagram of an emerging technology identification device based on scientific and technological information of the present invention; Figure 4 It is a schematic diagram of the structure of the computer device of the present invention. DETAILED DESCRIPTION

[0020] The technical solution of the present invention is further described in detail below through specific implementation methods.

[0021] It will be understood by those skilled in the art that, unless specifically stated, the singular forms "one", "an", "said" and "the" used herein may also include plural forms. It should be further understood that the terms "including" and "comprising" used in the embodiments of the present application mean that the corresponding features can be implemented as the presented features, information, data, steps, operations, elements and / or components, but do not exclude the implementation as other features, information, data, steps, operations, elements, components and / or combinations thereof supported by the technical field. It should be understood that when we say that an element is "connected" or "coupled" to another element, the one element may be directly connected or coupled to the other element, or it may refer to that the one element and the other element establish a connection relationship through an intermediate element. In addition, the "connection" or "coupling" used herein may include wireless connection or wireless coupling. The term "and / or" used herein indicates at least one of the items defined by the term, for example, "A and / or B" may be implemented as "A", or as "B", or as "A and B".

[0022] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0023] Example 1 The tobacco industry is an important part of the national economy, and scientific and technological innovation plays a vital supporting role in the high-quality development and modernization of the tobacco industry. At present, the tobacco industry faces both opportunities and challenges in terms of scientific and technological development. Under this background, research on emerging technology needs and technology forecasts at the industry level is conducted, especially in terms of identifying emerging technology fields, sorting out technical shortcomings, and forecasting future key technologies. This plays an important role in decision-making support for the formulation of strategic plans and overall layout related to scientific and technological innovation in the industry.

[0024] The embodiment of this application takes the tobacco field as an example to provide a specific implementation method of an emerging technology identification method based on scientific and technological information.

[0025] Figure 1 The flowchart of the emerging technology identification method based on scientific and technological information provided in the embodiment of the present application is shown in FIG. 1 . The execution subject of the method may be a device terminal or a server, etc. Figure 1 As shown, the emerging technology identification method based on scientific and technological information includes: Step S1, performing technical association mining on each text data in the tobacco field scientific and technological information data set to obtain at least one technology cluster.

[0026] Among them, the tobacco field science and technology information dataset includes text data corresponding to the scientific and technological achievements disclosed in the target field, such as paper texts, patent texts, fund project texts, book texts, and research report texts. This embodiment mainly constructs a science and technology information dataset based on domestic and foreign patent texts in the tobacco industry, where the patent text at least includes patent abstract text information. Specifically, the patent abstract text information includes: patentee, application date, inventor, IPC classification number, comparative documents, and specification abstract, etc.

[0027] Specifically, Figure 2 The figure is a flowchart of technical association mining in an example of an embodiment of the present application.

[0028] Step 101, such as Figure 2 As shown, the CRF model is used to extract the SAO triples of the patent abstract text, and SAO screening is performed based on the patent keywords generated by the large language model to obtain the SAO triples of each patent abstract text.

[0029] Among them, CRF (Conditional Random Fields) is a statistical model for sequence labeling and structured prediction tasks, which is used to extract SAO (Subject-Predicate-Object) triples.

[0030] The advantages of the SAO structure are mainly reflected in the following aspects: 1) Revealing deep semantic relationships and extracting high-dimensional information. Compared with ordinary keyword or topic extraction, the SAO structure can provide richer information dimensions and reveal deep semantic relationships in the text. For example, when processing patent documents, "using A to prepare B" (Subject: "A", Action: "Preparation", Object: "B") can reveal the application and output relationship between A and B, rather than simply identifying the technical action of "preparation", and provide a more comprehensive technical description through the combination of subject, predicate and object.

[0031] 2) Accurate information association. The SAO structure can more accurately identify related technologies and their functions or application scenarios. This is very important in the division of technology clusters and the identification of emerging technologies and core technologies, and can help researchers identify similarities and differences between technologies.

[0032] 3) Support complex query and analysis. In technology trend analysis or competitive intelligence analysis, researchers can construct complex queries based on the SAO structure to identify the actions and objects of specific subjects, thereby discovering potential technological innovations and technology routes.

[0033] 4) Enhanced semantic similarity calculation: When using semantic similarity to divide technology clusters, the SAO structure can provide more semantic feature points to help the calculation model identify subtle semantic connections between different documents, thereby improving the accuracy and efficiency of technology cluster division.

[0034] Therefore, this application extracts the SAO (Subject-Predicate-Object) triples in the patent abstract text and uses them as a basis to carry out in-depth technical identification work.

[0035] Specifically, in this embodiment, the specific steps of using the CRF model to label and extract SAO triples include: 1) Data preparation: Perform natural language processing preprocessing steps such as word segmentation, part-of-speech tagging, and named entity recognition on the patent abstract text to collect a text dataset containing SAO information.

[0036] 2) Feature Engineering: Select appropriate features for the CRF model, such as part of speech, entity type, contextual vocabulary, etc. These features help capture the information of SAO relations.

[0037] 3) Labeled data: Combine manual annotation with existing large language models to add SAO tags to the words in each sentence and generate feature vectors for each word and tag.

[0038] 4) Model training: Use the labeled dataset to train the conditional CRF model so that the CRF model learns to predict the SAO label of each word based on the input features and context.

[0039] 5) Predicting SAO relations: Run the trained CRF model on the unlabeled patent abstract text to predict the SAO label for each vocabulary.

[0040] Furthermore, some post-processing rules can be applied to the generated SAO triples to improve accuracy and consistency, for example, verifying the legitimacy of the SAO triples according to grammatical rules.

[0041] After SAO processing, the SAO triplet of each patent is obtained. The following table shows the SAO triplet of the patent.

[0042] Table 1 Patented SAO triples Patent ID Patent application number SAO Triplet 0 WO2015129098A1 [[('cigarette rawmaterials', 'beentreated with', 'alkali'), ('flavorcomponents', 'weretrapped in', 'closedspace')]] 1 BR112020011222A2 ['None', [('cartridge', 'include','compartment')], 'None', [('heater', 'have', 'sinusoidal -shaped member')], [('absorbent material', 'surround', 'sinusoidally shapedmember')], 'None'] 2 AU2019339246A1 [[('people', 'stop', 'smoking')], 'None',[('splitting section','separate', 'inhalation section'),('splitting section','separate', 'organicmatter combustionsection')], [('external atmosphericair', 'enter', 'inhalation section')],[('smoke', 'beinhaled', 'combustion')], 'None'] Step 102: semantically represent the SAO triples corresponding to each patent based on the Bert model, and merge synonyms of the SAO triples based on KMeans clustering.

[0043] It is understandable that BERT (Bidirectional Encoder Representations from Transformers) is a powerful language representation model that uses the Transformer architecture and undergoes large-scale unsupervised training to enable it to capture contextual semantic features. Representing SAO entities as high-dimensional vectors with the help of the BERT model is conducive to similarity calculation.

[0044] Specifically, the BERT model encodes the input text, where [CLS] represents the first token of a sentence and [SEP] represents the sentence separator. Through the processing of Token Embedding, Segment Embedding, and Position Embedding layers, BERT converts the text into a vector of fixed dimension and considers the contextual information of the sentence. Finally, a high-dimensional vector representation of each SAO entity is obtained, and then the cosine similarity is used to calculate the similarity of SAO phrases.

[0045] It should be noted that the text representation of SAO triples has inconsistent word representations, such as aerosol-generating article and aerosol-generating device, so synonym merging is required. The KMeans algorithm is a classic clustering algorithm, and its main use is to find the most representative data points, i.e., cluster centers, among a large number of high-dimensional data points. These cluster centers represent data of different categories, thereby achieving data classification. In this embodiment, the KMeans algorithm is used to cluster SAO entities to identify and merge synonyms.

[0046] Specifically, this embodiment uses the BERT model to represent SAO entities as high-dimensional vectors, so that each entity can compare their semantic similarities by calculating vector similarity, and then applies the KMeans algorithm to cluster these high-dimensional vectors into multiple cluster centers, each cluster center representing a class of similar entities. This process is iterated continuously until the cluster center no longer changes, and the similarity between each entity and each cluster center is calculated to determine whether to classify the entity into a specific cluster. If the similarity between the entity and a cluster center exceeds a predetermined threshold, it will be classified into the cluster. After being processed by this method, similar SAO entities can be classified into one category, realizing the synonym merging function, and increasing the density of the SAO network.

[0047] Step 103: construct a technology association network based on the association relationship of the SAO triples, and divide the technology clusters based on the graph theory community detection method.

[0048] Specifically, before dividing the technology clusters, based on the association relationship of SAO triples, NetworkX in Python is used to build a technology association network, and the associated SAO triples are connected through edges to form a graphical network structure. Then, the Louvain algorithm is applied to divide the technology clusters.

[0049] Among them, NetworkX is a Python library for creating, manipulating, and studying complex network structures. It is suitable for graph theory and network analysis, and provides rich graph data structures and many commonly used algorithms.

[0050] The Louvain algorithm is a community detection algorithm based on graph theory, which can identify communities or clusters formed by closely related nodes in the graph. The optimization goal of community or cluster division is to maximize the modularity of the entire community network. Iteratively build communities and observe the modularity of the entire community network. When the community modularity no longer changes, it means that the optimal community division is completed. It can be understood that in specific applications, each technology cluster can be regarded as a community containing similar SAO entities. The Louvain algorithm is used to cluster SAO entities with high correlation in the same technology cluster, thereby realizing the deep and fine-grained division and organization of text and semantic information, which is helpful for subsequent technology identification and analysis.

[0051] Step S2, such as Figure 1 As shown, the temporal novelty, innovative novelty, growth, technological impact, and social impact of the technology cluster are calculated based on the bibliographic data of each text data in each technology cluster.

[0052] Among them, the time novelty is used to characterize the average disclosure time of the scientific and technological achievements corresponding to the technology cluster; the innovation novelty is used to characterize the total number of citations of the scientific and technological achievements corresponding to the technology cluster; the growth is used to characterize the average growth rate of the scientific and technological achievements corresponding to the technology cluster; the technological impact is used to characterize the technology citations of the scientific and technological achievements corresponding to the technology cluster; and the social impact is used to characterize the total number of R&D personnel of the scientific and technological achievements corresponding to the technology cluster.

[0053] It is understandable that emerging technology (ET) was first proposed by the Emerging Technology Management Research Group of the Wharton School of the University of Pennsylvania. It refers to relatively fast-growing fundamental innovative technologies generated in the process of knowledge production, which have the potential to influence future economic and social development. Emerging technology is the source of power for technological renewal and innovation, which requires not only being "new" in time or space, but also "emerging" and "developing".

[0054] According to the research of domestic and foreign scholars, novelty, growth and impact are the key features for identifying emerging technologies. Therefore, this embodiment constructs the identification indicators of emerging technologies around these three features.

[0055] (1.1) Novelty Novelty is mainly considered from two dimensions: time and innovation, namely, temporal novelty and innovative novelty.

[0056] Among them, temporal novelty ( TN ) considers the time when the technology appeared. The later it appeared, the more it is an emerging technology. The calculation formula is shown in 2-1, where t i Indicates patents in technology clusters i The application year, n Represents the number of patents in a technology cluster.

[0057] (2-1) Innovation and novelty ( IN ) considers the content of the technology and the technical value reflected in the in-depth text content. The more patents a technology cites, the more knowledge it incorporates and the greater its innovation. The calculation formula is shown in 2-2, where C i Indicates patents in technology clusters i The number of cited patents, n Represents the number of patents in a technology cluster.

[0058] (2-2) (1.2) Growth "Emerging" represents the budding growth of new technologies, which grow faster than other technologies in the same field and are relative. The growth characteristics are mainly measured from the trend of technology clusters changing over time, using the average growth rate indicator. The calculation formula is shown in 2-3, where N T Indicates the time period divided, which is the time period of the technology cluster j The number of patents is the number of patents in a technology cluster over time. j-1 The number of patents.

[0059] (2-3) (1.3) Impact The significant impact of emerging technologies is reflected in both technical and social aspects. They will not only affect future technological trends, but also affect the entire industry and even people's lifestyles. Therefore, this embodiment measures the impact characteristics from two aspects: technical and social impact.

[0060] The number of technology citations can reflect the impact of technology ( TI ), this embodiment uses relative citation counts for correction, that is, the number of patent citations divided by the average number of citations of all patents granted in the same year, to eliminate the impact of patent age on citation frequency counts. The calculation formula is shown in 2-4, where B i,t Indicates patents in technology clusters i The number of citations, represents the average number of citations of all patents granted in the same year, n Represents the number of patents in a technology cluster.

[0061] (2-4) The number of researchers conducting research on emerging technologies can reflect social impact (SI). This embodiment uses the number of technology inventors to measure this feature. The calculation formula is shown in 2-5, where N p represents the number of patent holders, n Represents the number of patents in a technology cluster.

[0062] (2-5) Step S3, and obtaining the degree of emergence of the technology cluster based on the temporal novelty, innovative novelty, growth, technological impact, and social impact of the technology cluster.

[0063] Specifically, according to the first preset weight allocation rule, the temporal novelty, innovative novelty, growth, technological impact, and social impact of the patent are weighted and integrated to obtain the emerging score of the technology cluster.

[0064] In the specific implementation, in order to facilitate the comprehensive comparison of indicators and emerging scores, this embodiment performs a 0-1 standardization process on the above five indicators, and weights the indicators according to the dimension level, that is, obtains the first preset weight allocation rule, and then obtains the patent emerging score EScore1 according to the first preset weight allocation rule, and the formula is as follows:

[0065] in, a 1 、a 2 、a 3 、a 4 、a 5 The weight is reset for the first preset weight allocation rule.

[0066] It can be understood that the emerging score is the degree of emergence of the technology cluster. The higher the emerging score, the higher the degree of emergence of the technology cluster.

[0067] Of course, in other embodiments, after the emerging scores of each technology cluster are obtained, the emerging levels of the technology clusters are obtained according to the emerging scores of each technology cluster.

[0068] For example, the emerging scores are divided into multiple intervals in descending order, where the interval with the highest score is the first emerging level, and the second interval is the second emerging level. Then, the emerging level is determined by judging which interval the emerging scores of each technology cluster fall into.

[0069] Verification: Based on the emerging technology identification scheme in the previous part, the domestic patent technology of e-cigarettes in the tobacco field in the past 10 years is used as the verification set. The emerging technologies in e-cigarette technology are calculated based on the numerical values ​​of 5 indicators in the three dimensions of novelty, growth and influence, as shown in Table 2. Table 2 lists the 10 technology clusters with the highest scores.

[0070] It should be noted that after 0-1 standardization, the score range of each indicator is [0,1]. The closer the score is to 1, the higher the characteristics of the technology are compared with other technologies.

[0071] Table 2 Top 10 emerging technology clusters by score cluster Temporal novelty (TN) Innovation Novelty (IN) Growth (R) Technology Impact (TI) Social Impact (SI) Emerging Score (EScore) C55 0.627 1.000 0.588 1.000 1.000 2.402 C445 0.793 0.003 0.997 0.006 0.007 1.402 C434 0.635 0.008 0.855 0.008 0.007 1.184 C142 0.733 0.021 0.631 0.017 0.031 1.032 C625 0.739 0.051 0.569 0.056 0.050 1.017 C394 0.637 0.015 0.636 0.033 0.030 0.994 C35 0.627 0.049 0.577 0.046 0.066 0.971 C35 0.607 0.130 0.461 0.132 0.141 0.966 C41 0.667 0.151 0.448 0.076 0.099 0.945 It can be seen that the emerging score of technology cluster C55 is the highest, with the highest scores in terms of innovation impact, technical impact and social impact. Its emerging characteristics are also highlighted in the dimension of temporal novelty, and its score in terms of growth is at a medium level, indicating that the development of this technology cluster has reached a certain stage, accumulated a lot of influence, and is currently receiving widespread attention, with a sustained and stable output of patents. Technology cluster C445 has a high temporal novelty and growth rate, and is a technology point that has received attention recently, so its technical impact and social impact are still relatively low.

[0072] Table 3 lists the 5 representative SAO triple information corresponding to these 10 technology clusters. Among them, the representative triples are selected according to the in-degree and occurrence frequency of the SAO nodes to assist in the positioning of all triple information.

[0073] Table 3 Representative SAO triples of the top 10 emerging scoring technology clusters cluster Represents SAO triple C55 Atomizer|||Including|||Liquid storage component; Atomizer|||Including|||Base assembly; Atomizer|||Including|||Liquid storage assembly; Atomizer|||Including|||Atomizing element C445 Atomization carrier|||Damage|||Inside of electronic cigarette; Atomization liquid carrier|||Including|||Second contact part; Atomization medium|||Meet|||Safety standard; Oil-blocking body|||Adsorb|||Atomization medium C434 The cartridge|||has|||a second part; the winding|||includes|||a third part; the first part|||includes|||a first material; the second part|||exposes|||a storage compartment; the heating core|||includes|||a second part C142 Aerosol generator|||including|||surface acoustic wave nebulizer; aerosol generator|||including|||surface acoustic wave nebulizer; ceramic nebulizer|||including|||heat-generating medium; glass nebulizer|||having|||smooth surface; surface acoustic wave nebulizer|||including|||active surface C625 Aerosol generator|||including|||gas-electric hybrid joint;Aerosol generator|||including|||gas-electric hybrid joint;Solvent reflux capture device|||increase|||substance concentration;Solvent reflux capture device|||save|||solvent usage C394 Connecting hole|||Return|||Oil-blocking silicone;Connecting hole|||Return|||Oil-blocking silicone;Atomizing upper seat|||Located at|||Horizontal through hole;Connecting hole|||Higher than|||Condensation chamber;E-liquid bottle|||Has|||First oil storage chamber C35 Atomizer|||with||suction nozzle;front end|||with||suction nozzle;capsule|||with||suction nozzle;sliding cover|||covering|||suction nozzle;suction nozzle|||with|||suction opening C35 Atomizer|||convenient|||smoke oil; atomizer|||appears|||leakage; oil storage bottle|||contains|||smoke oil; oil guide|||absorbs|||smoke oil; oil reservoir|||transports|||smoke oil C41 The cartridge|||reduces|||the oil; the cartridge|||includes|||the airway; the cartridge|||has|||seal; the cartridge|||includes|||the cartridge bin; the cartridge|||includes|||the oil tank C257 Atomizer|||Including|||Atomizing shell; Single chip microcomputer|||Adjustment|||Atomizing wire; Atomizing oil|||Infiltration|||Oil absorbing cotton; Atomizing sheet|||Including|||Third side; Air energy|||Passing|||Atomizing sheet Based on the representative SAO triplet information positioning of technology cluster C55, the SAO triplet information and patent literature were read to supplement the information, and the technology cluster was summarized as electronic cigarette atomization technology. The SAO information includes the atomizer covering multiple key components such as liquid storage parts, base components, liquid delivery elements, sensor elements, smoke channels, ultrasonic oscillation plates, etc.

[0074] Based on the SAO network diagram of technology cluster C445, the core technology points are located, and the SAO triple information and patent literature are read to supplement the information. The technology cluster can be summarized as solid atomization medium optimization technology. SAO information includes the structure and material of solid atomization medium, as well as storage space design.

[0075] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0076] Example 2 The difference between this embodiment and embodiment 1 is that this embodiment mainly constructs a scientific and technological information data set based on domestic and foreign paper data of the tobacco industry, wherein the paper data at least includes paper bibliographic information. Specifically, the bibliographic information refers to the basic information of the document, for example, the basic information of the paper includes publication time, title, author, keywords, author organization, document source and abstract, etc.

[0077] Specifically, Figure 1 As shown, the emerging technology identification method based on scientific and technological information includes: Step S1, performing technical association mining on each paper data in the tobacco field scientific and technological information data set to obtain at least one technology cluster.

[0078] It should be noted that paper abstracts are usually filled with a lot of background information, and because they contain multiple lengthy sentences, the SAO structure is difficult to understand intuitively. This not only hinders the accurate calculation of SAO structural similarity, but also affects the accuracy of technology cluster division.

[0079] To solve this problem, this embodiment extracts keywords from the front part of the paper, and automatically extracts paper keywords from the paper abstract as a supplement, thereby constructing a keyword vocabulary for the technical field, namely, the field paper keyword vocabulary.

[0080] like Figure 2 As shown, the specific steps of step S1 are: The SAO triples of the paper text are extracted by using text mining methods, and SAO screening is performed based on the paper keywords to obtain the SAO triples of each paper; among which, the paper keywords are the paper keywords in the field paper keyword vocabulary; Table 4 shows the SAO information after paper screening. It can be seen that the SAO structure becomes more concise and clear after keyword filtering. This not only retains the key technical points to a large extent, but also clearly shows the relationship between the technical points.

[0081] Table 4 SAO information after paper screening Paper ID Title SAO Field 0 Synthesis and Antibacterial Activity of Symmetrical Gemini Quaternary Ammonium Salts Containing Hydronopyl [["Methylhydrogenolpylamine","synthesis","gemini quaternary ammonium salt"],["Methylhydrogenolpylamine","synthesis","symmetric"], ["ethyl","synthesis","symmetric"], ["diethylhydrogenolpylamine","synthesis","symmetric"], ["hydrogenolpyl","synthesis","gemini quaternary ammonium salt"],["compound","has","inhibitory effect"], ["compound","is","ethyl"], ["compound","contains","ethyl"]] 1 Hyperspectral inversion model of pectin under salt and physical damage stress in wheat [["Physical damage", "becomes","wheat yield"], ["Physical damage", "becomes", "wheat"],["Physical damage", "leads to", "nutrients"], ["Pectin", "composition", "main component of plant cell wall"], ["Linear regression", "established", "pectin"]] 2 Screening of compound biocontrol bacteria against tobacco gray mold [["Control effect", "Belongs to", "Pseudomonas"],["Strain", "Belongs to", "Pseudomonas"]] The SAO triples corresponding to each paper are semantically represented based on the Bert model, and the synonyms of SAO triples are merged based on KMeans clustering; A technology association network is constructed based on the association relationship of SAO triplets, and technology clusters are divided based on the graph theory community detection method.

[0082] Step S2, based on at least one paper text in each technology cluster, obtain the temporal novelty, growth, and social impact of the paper.

[0083] Due to the limitations of citation and cited data in paper data, this embodiment retains the attributes of emerging technologies in the three dimensions of novelty, growth and impact when analyzing paper data, and reduces the number of indicators, that is, evaluating novelty attributes from the perspective of temporal novelty, growth rate to evaluate growth attributes, and social impact to evaluate impact attributes. Specifically, the temporal novelty, growth, and social impact of the paper refer to the aforementioned method for obtaining the temporal novelty, innovative novelty, growth, technological impact, and social impact of the patent. It only requires that the information related to the patent be modified to the information related to the paper, such as modifying the patent application time to the paper publication time, and modifying the patent inventor to the paper author, etc., which will not be repeated here.

[0084] Step S3, obtaining the degree of emergence of the technology cluster based on the temporal novelty, growth, and social impact of the technology cluster.

[0085] The specific steps are: according to the second preset weight allocation rule, the temporal novelty, growth, and social impact of the paper are weighted and integrated to obtain the emerging score of the technology cluster.

[0086] Similarly, in order to facilitate comprehensive comparison of indicators and emerging scores, this embodiment performs a 0-1 standardization process on the above-mentioned time novelty, growth, and social impact, and weights the indicators according to the dimension level, that is, obtains the second preset weight allocation rule, and then according to the second preset weight allocation rule, weights the time novelty, growth, and social impact of the paper to obtain the emerging score EScore2 of the technology cluster. The formula is as follows: .

[0087] in, b 1 、b 2 、b 3 The weight is reset for the second preset weight allocation rule.

[0088] Verification: Based on the emerging technology identification scheme in the previous section, domestic papers (including journals and conference papers) in the tobacco field in the past 10 years were used as the verification data set for verification. Table 5 lists the 10 technology clusters with the highest scores.

[0089] Table 5 Top 10 emerging technology clusters by score cluster Novelty (TN) Growth (R) Impact (SI) Emerging Score (EScore) C16 0.555 0.284 1.000 1.839 C1222 0.613 0.972 0.031 1.616 C635 0.566 1.000 0.013 1.579 C1677 0.923 0.607 0.004 1.534 C62 0.560 0.272 0.616 1.447 C33 0.633 0.779 0.012 1.424 C882 0.577 0.807 0.011 1.395 C2252 0.657 0.714 0.010 1.380 C154 0.638 0.717 0.022 1.377 C222 0.643 0.723 0.004 1.370 Similarly, after 0-1 standardization, the score range of each indicator is [0,1]. The closer the score is to 1, the higher the characteristics of the technology are compared with other technologies.

[0090] Table 6 lists the 5 representative SAO triple information corresponding to these 10 technology clusters. Among them, the representative triples are selected according to the in-degree and occurrence frequency of the SAO nodes to assist in the positioning of all triple information.

[0091] Table 6 Representative SAO triples of the top 10 emerging scoring technology clusters cluster Represents SAO triple C16 Shandong China Tobacco|||Implementation|||Working meeting; Tobacco direct-sale stores|||Learn from|||chain retail enterprises; Sichuan Tobacco|||Introduced|||Mobile law enforcement terminals; Dust explosion|||Occurred|||Manufacturing enterprises; Tobacco departments|||Give full play to|||Retired Party members C1222 Bemisia tabaci|||transmission|||plant viruses; Bemisia tabaci|||distribution|||upper leaves; yellow light|||improves|||bemisia tabaci; Bemisia tabaci|||inhibits|||insect resistance; Colletotrichum oleraceus|||infection|||strawberry C635 green fluorescence|||enriched|||middle part;azelaic acid|||induced|||plant resistance;azelaic acid|||has|||plant root system;green fluorescence|||enriched|||middle part;Agrobacterium injection|||observation|||green fluorescence C1677 Differential metabolites|||including||flavonoids;nitropyrrolidine|||is||positively regulated;nitropyrrolidine|||is||positively regulated;network pharmacology|||predicts|||differential metabolites;differential metabolites|||enrichment|||degradation pathways C62 Different brands||| have||| obvious differences; mutants||| are beneficial to||| metabolic regulation; tobacco brown spot disease||| causes||| intercellular CO2 concentration; the encoded protein||| exists||| conservative; quinclorac||| produces||| phytotoxicity C33 Different maturity||| is in the early stage of color fixation; Chlorophyll b||| causes||| saturation; Dry tobacco||| reduces||| during the dry period; Chlorophyll b||| is higher than||| altitude gradient; Different maturity||| has||| obvious differences C882 Congressional panel|||published|||workplace;zoning|||as|||control area;zoning|||as|||control area;workplace|||became|||occupational health;monitored|||supported|||workplace C2252 The preventive effect|||is better than the therapeutic effect; Bacillus|||has|||biological control effect; The preventive effect|||is better than|||the therapeutic effect; Toosendanin|||has|||anti-tumor drug; Toosendanin|||has|||anti-tumor drug C154 Development period|||Influence|||Cat stink bug;Deltamethrin|||Control|||Tobacco budworm;Nymph|||Behavior|||Preference;Nymph|||Behavior|||Preference;Ceratitis scabra|||Influence|||Predation behavior C222 Government departments|||issue|||smoking control regulations; monitoring results|||show|||smoking control regulations; smoking control regulations|||lead to|||brand promotion; research and development expenses|||regulate|||wholesale and retail industries; smoking control regulations|||favor|||public participation It can be seen that technology cluster C124 has the highest emerging score and the highest score in terms of technological impact. It also highlights its emerging characteristics in the dimension of time novelty, and its emerging characteristics are not obvious in the dimension of growth, indicating that this technology cluster has more papers with more social attention. Based on the representative SAO triple information positioning of technology cluster C124, the SAO triple information and paper literature are read to supplement the information, and the technology cluster is summarized as flue-cured tobacco ecological optimization and quality improvement technology. SAO information includes biochar suitable for flue-cured tobacco, air blowing technology, cash crops, marigold stems, etc.

[0092] Example 3 Based on the same inventive concept, the embodiment of the present application also provides an emerging technology identification device based on scientific and technological information for implementing the above-mentioned emerging technology identification method based on scientific and technological information. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above-mentioned method, so the specific limitations in one or more embodiments of the emerging technology identification device based on scientific and technological information provided below can refer to the limitations of the emerging technology identification method based on scientific and technological information in the above embodiment 1 or embodiment 2, and will not be repeated here.

[0093] Specifically, the emerging technology identification device based on scientific and technological information is as follows: Figure 3 As shown, including: A technology cluster acquisition module is used to perform technology association mining on each text data in the target field science and technology information data set to obtain at least one technology cluster; wherein the science and technology information data set includes text data corresponding to the scientific and technological achievements disclosed in the target field; A technology cluster index acquisition module is used to calculate the temporal novelty, innovative novelty, growth, technological impact, and social impact of the technology cluster based on the bibliographic data of each text data in each technology cluster; wherein the temporal novelty is used to characterize the average disclosure time of the scientific and technological achievements corresponding to the technology cluster; the innovative novelty is used to characterize the total number of citations of the scientific and technological achievements corresponding to the technology cluster; the growth is used to characterize the average growth rate of the scientific and technological achievements corresponding to the technology cluster; the technological impact is used to characterize the number of technology citations of the scientific and technological achievements corresponding to the technology cluster; and the social impact is used to characterize the total number of R&D personnel of the scientific and technological achievements corresponding to the technology cluster; The module for acquiring the degree of technological emergence acquires the degree of emergence of the technology cluster based on the temporal novelty, innovative novelty, growth, technological impact, and social impact of the technology cluster.

[0094] Example 4 Based on the above embodiment, this embodiment provides a computer device, which may be a terminal, and its internal structure diagram may be as follows: Figure 4As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, it implements an emerging technology identification method based on scientific and technological information described in Example 1. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0095] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0096] Example 5 On the basis of the above embodiments, this embodiment provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the emerging technology identification method based on scientific and technological information as described in Example 1 is implemented.

[0097] Example 6 On the basis of the above embodiments, this embodiment provides a computer program product, including a computer program, which, when executed by a processor, implements the emerging technology identification method based on scientific and technological information as described in Embodiment 1.

[0098] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0099] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0100] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

[0101] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or some technical features can be replaced by equivalents without departing from the spirit of the technical solution of the present invention, which should be included in the scope of the technical solution for protection of the present invention.

Claims

1. A method for identifying emerging technologies based on scientific and technological information, characterized in that: The following steps are involved: Performing technical association mining on each text data in the target field science and technology information data set to obtain at least one technology cluster; wherein the science and technology information data set includes text data corresponding to the scientific and technological achievements disclosed in the target field; Calculate the temporal novelty, innovative novelty, growth, technological impact, and social impact of the technology cluster based on the bibliographic data of each text data in each technology cluster; Among them, the time novelty is used to characterize the average publication time of the scientific and technological achievements corresponding to the technology cluster; the innovation novelty is used to characterize the total number of citations of the scientific and technological achievements corresponding to the technology cluster; the growth is used to characterize the average growth rate of the scientific and technological achievements corresponding to the technology cluster; the technological impact is used to characterize the technology citations of the scientific and technological achievements corresponding to the technology cluster; the social impact is used to characterize the total number of R&D personnel of the scientific and technological achievements corresponding to the technology cluster; The degree of emergence of the technology cluster is obtained based on the temporal novelty, innovative novelty, growth, technological impact and social impact of the technology cluster.

2. The emerging technology identification method based on scientific and technological information according to claim 1 is characterized in that: Based on the bibliographic data of each text data in the target field science and technology information dataset, the temporal novelty, innovation novelty, growth, technological impact, and social impact of each technology cluster are calculated, including: Based on the publication time and number of the published texts of the text data in the technology cluster, obtaining the temporal novelty of the technology cluster; Based on the number of texts cited by the text data in the technology cluster, the innovation novelty of the technology cluster is obtained; Based on the amount of text in the text data of the technology cluster in different time periods, obtaining the growth of the technology cluster; Based on the number of citations of text data in the technology cluster and the number of citations of all patents authorized in the same year, the technical impact of the technology cluster is obtained; Based on the amount of text data in the technology cluster and the corresponding number of R&D personnel, the social influence of the technology cluster is obtained.

3. The emerging technology identification method based on scientific and technological information according to claim 1 or 2, characterized in that: The scientific and technological achievements disclosed in the target field are patents; The calculation of the temporal novelty, innovative novelty, growth, technological impact, and social impact of the technology cluster based on the bibliographic data of each text data in each technology cluster includes: Based on at least one patent text in each technology cluster, obtain the temporal novelty, innovative novelty, growth, technological impact, and social impact of the technology cluster; The method of obtaining the emerging degree of the technology cluster based on the temporal novelty, innovative novelty, growth, technological impact, and social impact of the technology cluster includes: According to the first preset weight allocation rule, the temporal novelty, innovative novelty, growth, technological impact, and social impact of the patent are weighted and integrated to obtain the emerging score of the technology cluster.

4. The emerging technology identification method based on scientific and technological information according to claim 1 or 2, characterized in that: The scientific and technological achievements disclosed in the target field are papers; The calculation of the temporal novelty, innovative novelty, growth, technological impact, and social impact of the technology cluster based on the bibliographic data of each text data in each technology cluster includes: Based on at least one paper text in each technology cluster, obtain the temporal novelty, growth, and social impact of the technology cluster; The method of obtaining the emerging degree of the technology cluster based on the temporal novelty, innovative novelty, growth, technological impact, and social impact of the technology cluster includes: According to the second preset weight allocation rule, the temporal novelty, growth, and social impact of the paper are weighted and integrated to obtain the emerging score of the technology cluster.

5. The emerging technology identification method based on scientific and technological information according to claim 3 is characterized in that: Perform technical association mining on each text data in the target field science and technology information dataset to obtain at least one technology cluster, including: The CRF model is used to extract SAO triples from the patent abstract text, and SAO is screened based on the patent keywords generated by the large language model to obtain the SAO triples of each patent. The SAO triples corresponding to each patent are semantically represented based on the Bert model, and synonyms of SAO triples are merged based on KMeans clustering; A technology association network is constructed based on the association relationship of SAO triplets, and technology clusters are divided based on the graph theory community detection method.

6. The emerging technology identification method based on scientific and technological information according to claim 4 is characterized in that: Perform technical association mining on each text data in the target field science and technology information dataset to obtain at least one technology cluster, including: The SAO triples of the paper text are extracted by using text mining methods, and SAO screening is performed based on the paper keywords to obtain the SAO triples of each paper; the paper keywords are the paper keywords in the field paper keyword vocabulary, and the field paper keyword vocabulary is constructed by extracting the paper keywords in the paper text bibliography and extracting the paper keywords in the paper abstract; The SAO triples corresponding to each paper are semantically represented based on the Bert model, and the synonyms of SAO triples are merged based on KMeans clustering; A technology association network is constructed based on the association relationship of SAO triplets, and technology clusters are divided based on the graph theory community detection method.

7. An emerging technology identification device based on scientific and technological information, characterized in that: include: A technology cluster acquisition module is used to perform technology association mining on each text data in the target field science and technology information data set to obtain at least one technology cluster; wherein the science and technology information data set includes text data corresponding to the scientific and technological achievements disclosed in the target field; A technology cluster index acquisition module is used to calculate the temporal novelty, innovative novelty, growth, technological impact, and social impact of the technology cluster based on the bibliographic data of each text data in each technology cluster; wherein the temporal novelty is used to characterize the average disclosure time of the scientific and technological achievements corresponding to the technology cluster; the innovative novelty is used to characterize the total number of citations of the scientific and technological achievements corresponding to the technology cluster; the growth is used to characterize the average growth rate of the scientific and technological achievements corresponding to the technology cluster; the technological impact is used to characterize the number of technology citations of the scientific and technological achievements corresponding to the technology cluster; and the social impact is used to characterize the total number of R&D personnel of the scientific and technological achievements corresponding to the technology cluster; The module for acquiring the degree of technological emergence acquires the degree of emergence of the technology cluster based on the temporal novelty, innovative novelty, growth, technological impact, and social impact of the technology cluster.

8. A computer device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; Memory, used to store computer programs; A processor is used to implement the emerging technology identification method based on scientific and technological information as described in any one of claims 1 to 6 when executing a program stored in a memory.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for identifying emerging technologies based on scientific and technological information as described in any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for identifying emerging technologies based on scientific and technological information as described in any one of claims 1 to 6 is implemented.

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