A hotspot technology analysis system and method

Abstract

The application discloses a hot technology analysis system and analysis method, and belongs to the technical field of information processing. The system comprises an intelligence resource database which stores a plurality of literatures to be analyzed for hot technology; a hot technology keyword extraction module which is used for extracting a plurality of keywords related to hot technology from the literatures; a hot technology correlation degree analysis module which is used for determining the correlation value between hot technology and other hot technology; a hot technology importance analysis module which determines the academic influence value of hot technology; a hot technology difficulty analysis module which determines the technical complexity of hot technology; and a hot technology merge sorting module which merges hot technology meeting a first preset condition into the same technology group and sorts the hot technology in the same technology group. The system can more scientifically and reasonably reflect the internal logical connection on the technology layout.

Description

Technical Field

[0001] This invention belongs to the field of information processing technology, and in particular relates to a hot topic technology analysis system and method. Background Technology

[0002] Technology roadmaps, as a strategic planning and forecasting method, have become an important tool for technology path planning and technology development layout. They provide crucial support for predicting the direction of technological development and assisting in planning.

[0003] Demonstrating and formulating a technology development roadmap requires screening, analyzing, merging, and prioritizing the hot technologies in the field. Identifying these hot technologies is crucial to the accuracy and guiding significance of the final technology roadmap.

[0004] With the development and improvement of technology roadmap methods and theories, techniques such as SWOT analysis, correlation analysis, bibliometrics, data-driven fitting and prediction, and related mathematical statistics are applied to the selection and analysis of hot technologies. However, overall, there are still many problems with the methods for screening, analyzing, and merging hot technologies, for example:

[0005] 1. The analysis and ranking of hot technologies still rely too much on expert experience and are judged by questionnaire scoring and statistics. The subjective experience of experts and the knowledge barriers of experts in different technical fields can easily lead to a certain degree of non-objectivity in the results.

[0006] 2. There is a lack of unified consideration of the importance, difficulty, and interrelationships of hot technologies, and the impact of various factors on the layout of technology development is not fully reflected.

[0007] 3. The lack of automated analysis systems means that the demonstration and analysis process consumes a lot of human and material resources, resulting in high costs. Summary of the Invention

[0008] This invention provides a hotspot technology analysis system and method to solve the above-mentioned problems or at least partially solve the above-mentioned problems.

[0009] Firstly, a hotspot technology analysis system is disclosed, the system comprising:

[0010] The system includes an intelligence resource database, a hot technology keyword extraction module, a hot technology correlation analysis module, a hot technology importance analysis module, a hot technology difficulty analysis module, and a hot technology merging and sorting module.

[0011] The intelligence resource database is used to store multiple documents for hot technology analysis; the hot technologies are multiple.

[0012] The hot technology keyword extraction module is used to extract multiple keywords related to hot technologies from the literature, normalize the keywords based on text similarity, and establish a mapping relationship between keywords, literature, and hot technologies. The normalization means that for multiple keywords with text similarity greater than a first preset threshold, only one keyword is retained, and the other unretained keywords are replaced with the retained keyword.

[0013] The hot technology correlation analysis module is used to construct feature vectors corresponding to each hot technology. The feature vectors are composed of all the keywords corresponding to the hot technology. For each hot technology, the correlation value between the hot technology and other hot technologies is determined based on the similarity between its corresponding feature vector and the feature vectors corresponding to other hot technologies. The correlation value represents the similarity between the hot technology and other hot technologies.

[0014] The hot technology importance analysis module obtains all the literature corresponding to each hot technology; for each hot technology, the academic influence value of the hot technology is determined based on the impact factor and citation data of all the literature corresponding to the hot technology within a preset time period.

[0015] The module for analyzing the difficulty of hot technologies determines the number of documents corresponding to each hot technology in each year within the preset time period. It then combines the impact factor weight of the technology research and development trend in each year to determine the publication trend of the hot technology within the preset time period. Based on the publication trend, it determines the technical complexity of the hot technology.

[0016] The hot technology merging and sorting module determines the comprehensive correlation influence value of each hot technology relative to other hot technologies based on the correlation value between the hot technology and other hot technologies, the academic influence value corresponding to the hot technology, and the technical complexity. Hot technologies that meet the first preset conditions are merged into the same technology group, and the hot technologies in the same technology group are sorted.

[0017] Preferably, for each hot technology, a correlation value is determined between the hot technology and other hot technologies based on the similarity between its corresponding feature vector and the feature vectors corresponding to other hot technologies. This correlation value characterizes the similarity between the hot technology and other hot technologies. The formula for calculating the correlation value between the hot technology and other hot technologies is as follows:

[0018]

[0019] Among them, Sr m,m′ N represents the correlation value between the m-th hot technology and the m′-th hot technology. m,m′N represents the number of keywords that are common between the m-th and m′-th trending technologies. m′ Let N be the number of keywords for the m′-th trending technology. m Let m be the number of keywords for the m-th hot technology, 1≤m, m′≤M, and m≠m′.

[0020] Preferably, the hot technology importance analysis module acquires all literature corresponding to each hot technology; for each hot technology, the academic impact value of the hot technology is determined based on the impact factor and citation data of all literature corresponding to the hot technology within a preset time period, wherein:

[0021]

[0022] Is m Let m be the academic influence of the m-th hot technology. For the m-th hot technology, the l-th... m The impact factor of the article For the m-th hot technology, the l-th... m The number of citations of a document, l m =1,2,3,...,L m L m The total number of documents corresponding to the m-th hot technology;

[0023] The academic impact value of this trending technology is determined by the following formula:

[0024]

[0025] Among them, Si m Let Is be the academic impact value of the m-th hot technology. max This represents the maximum academic impact of all trending technologies.

[0026] Preferably, the hot technology difficulty analysis module determines, for each hot technology, the number of publications corresponding to that hot technology in each year within the preset time period, and combines this with the weight of the technology research and development trend impact factor for each year to determine the publication volume trend of that hot technology within the preset time period. Based on the publication volume trend, the technical complexity of that hot technology is determined, wherein:

[0027]

[0028] Ns m This refers to the trend of the number of articles published on the m-th trending technology within the preset time period, where the preset time period corresponds to X years, x = 1, 2, 3, ..., X. Let m be the number of publications corresponding to the m-th hot technology in year x. The weight of the technological research and development trend influence factor for the m-th hot technology in year x is set based on the overall development trend of the technological field in which the m-th hot technology is located and the expert judgment value, satisfying the following conditions. and

[0029] The technical complexity is as follows:

[0030]

[0031] Among them, Sd m Let Ns be the technical complexity of the m-th hot technology. max This represents the maximum number of articles published on all trending technologies over the past X years.

[0032] Preferably, the hotspot technology merging and sorting module performs the following operations for each hotspot technology:

[0033] calculate

[0034] S m,m′ Let λ be the comprehensive correlation influence value of the m-th hot technology relative to the m′-th hot technology. m,m′ μ m,m′ and ν m,m′ Let be the weight parameters, and satisfy λ. m,m′ +μ m,m′ +ν m,m′ =1;

[0035] Calculate S m,m′ The corresponding mean and variance, and then S m,m′ Standardize the data:

[0036]

[0037]

[0038] The S m,m′ Data standardization includes: calculation S m,m′ Assigned value in, For S m,m′ The corresponding mean, Sq m The corresponding variance;

[0039] Calculate the covariance matrix of the standardized results:

[0040]

[0041] Among them, cov(S m ,S m′)=E(S m S m′ )-E(S m E(S) m′ E(·) is the mean function, and S m =[S m,1 ,S m,2 ,S m,3 ,...,S m,M ], S m' =[S m',1 ,S m',2 ,S m',3 ,...,S m',M ], S m In the middle, S m,m =1; S m' In the middle, S m',m' =1;

[0042] Solve the characteristic equation |λ m IC|=0, thus obtaining the eigenvalue λ m , where I is the identity matrix.

[0043] Preferably, after obtaining the feature values ​​corresponding to each hot technology, the feature values ​​are arranged in descending order, and the sorting result is recorded as the sorting sequence {λ1',λ2',...,λ'}. M} Calculate the feature vector e' corresponding to each element in the sorted sequence. m , satisfying ||e' m || = 1;

[0044] Calculate the contribution rate of each element in the sorted sequence:

[0045]

[0046] Obtain the hotspot technologies corresponding to elements with a contribution rate greater than 0.9 in the sorted sequence, and then extract the feature vector e' corresponding to all the hotspot technologies. m In the process, select the feature vector e' m Hot technologies whose components are all positive are considered hot technologies that meet the first preset condition. These hot technologies are then merged into a technology group, and all hot technologies in the technology group are sorted from largest to smallest according to their comprehensive correlation impact value.

[0047] Secondly, a hot topic technology analysis method is disclosed, based on the hot topic technology analysis system described above, the method comprising:

[0048] Step S1: Obtain literature on the technical field to be demonstrated and store it in the intelligence resource database of the hotspot analysis system;

[0049] Step S2: The hotspot analysis system performs hotspot analysis on the literature of the technical field to be demonstrated, and obtains a technology group;

[0050] Step S3: Based on the technology group, determine the technical route in this technical field.

[0051] Thirdly, an electronic device is disclosed, the electronic device comprising:

[0052] At least one processor; and

[0053] A memory communicatively connected to the at least one processor; wherein,

[0054] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method as described above.

[0055] Fourthly, a non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform the method described above is disclosed.

[0056] The present invention has the following technical effects:

[0057] 1. This invention is mainly based on the analysis and measurement of objective literature data, avoiding the subjectivity of expert experience and the analytical bias caused by the knowledge barriers of experts in different technical fields. It can be combined with questionnaire-based argumentation methods based on expert knowledge and brainstorming to achieve the integration of expert knowledge and objective data and improve the credibility of the results.

[0058] 2. The hot technology analysis system and implementation method proposed in this invention comprehensively consider the relationship between hot technologies, the importance and difficulty of hot technology development, and the merging and sorting of hot technologies through the coupling relationship among the three, which can more scientifically and rationally reflect the internal logical connection in the technology layout.

[0059] 3. The hot technology analysis system proposed in this invention has a simple structure and low computational complexity. It can quickly and automatically perform hot technology analysis, and its modular design enables the parallel operation of some functions, effectively reducing the cost of technology roadmap demonstration and improving its effectiveness. Attached Figure Description

[0060] Figure 1 This is a schematic diagram of the architecture of a hot technology analysis system;

[0061] Figure 2 This is a schematic diagram of another embodiment of the hotspot technology analysis system. Detailed Implementation

[0062] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0063] like Figures 1-2 As shown, the present invention provides a hotspot technology analysis system, the system comprising:

[0064] The system includes an intelligence resource database, a hot technology keyword extraction module, a hot technology correlation analysis module, a hot technology importance analysis module, a hot technology difficulty analysis module, and a hot technology merging and sorting module.

[0065] The intelligence resource database is used to store multiple documents for hot technology analysis; the hot technologies are multiple.

[0066] The hot technology keyword extraction module is used to extract multiple keywords related to hot technologies from the literature, normalize the keywords based on text similarity, and establish a mapping relationship between keywords, literature, and hot technologies. The normalization means that for multiple keywords with text similarity greater than a first preset threshold, only one keyword is retained, and the other unretained keywords are replaced with the retained keyword.

[0067] The hot technology correlation analysis module is used to construct feature vectors corresponding to each hot technology. The feature vectors are composed of all the keywords corresponding to the hot technology. For each hot technology, the correlation value between the hot technology and other hot technologies is determined based on the similarity between its corresponding feature vector and the feature vectors corresponding to other hot technologies. The correlation value represents the similarity between the hot technology and other hot technologies.

[0068] The hot technology importance analysis module obtains all the literature corresponding to each hot technology; for each hot technology, the academic influence value of the hot technology is determined based on the impact factor and citation data of all the literature corresponding to the hot technology within a preset time period.

[0069] The module for analyzing the difficulty of hot technologies determines the number of documents corresponding to each hot technology in each year within the preset time period. It then combines the impact factor weight of the technology research and development trend in each year to determine the publication trend of the hot technology within the preset time period. Based on the publication trend, it determines the technical complexity of the hot technology.

[0070] The hot technology merging and sorting module determines the comprehensive correlation influence value of each hot technology relative to other hot technologies based on the correlation value between the hot technology and other hot technologies, the academic influence value corresponding to the hot technology, and the technical complexity. Hot technologies that meet the first preset conditions are merged into the same technology group, and the hot technologies in the same technology group are sorted.

[0071] In this invention, M hot technologies in the technical field to be demonstrated are analyzed. A hot technology keyword extraction module retrieves relevant literature on these technologies within X years (the timeframe can be set according to specific needs) from an information resource database. Keywords are extracted through text extraction, and identical keywords are merged using text alignment and disambiguation, unifying them into a single keyword name. After keyword unification, a mapping relationship is established between keywords, literature resources, and hot technologies. The number of documents retrieved for the m-th hot technology is L. m The number of keywords extracted from the m-th hot technology is N. m , where m=1,2,3,...,M.

[0072] Furthermore, for each hot technology, a correlation value is determined between it and other hot technologies based on the similarity between its corresponding feature vector and the feature vectors corresponding to other hot technologies. This correlation value characterizes the similarity between the hot technology and other hot technologies. The formula for calculating the correlation value between the hot technology and other hot technologies is as follows:

[0073]

[0074] Among them, Sr m,m′ N represents the correlation value between the m-th hot technology and the m′-th hot technology. m,m′ N represents the number of keywords that are common between the m-th and m′-th trending technologies. m′ Let N be the number of keywords for the m′-th trending technology. m Let m be the number of keywords for the m-th hot technology, 1≤m, m′≤M, and m≠m′.

[0075] The hot technology importance analysis module obtains all literature corresponding to each hot technology; for each hot technology, the academic impact value of the hot technology is determined based on the impact factor and citation data of all literature corresponding to the hot technology within a preset time period, wherein:

[0076]

[0077] Is m Let m be the academic influence of the m-th hot technology. For the m-th hot technology, the l-th... m The impact factor of the article For the m-th hot technology, the l-th... m The number of citations of a document, l m =1,2,3,...,L m L m The total number of documents corresponding to the m-th hot technology;

[0078] The academic impact value of this trending technology is determined by the following formula:

[0079]

[0080] Among them, Si m Let Is be the academic impact value of the m-th hot technology. max This represents the maximum academic impact of all trending technologies.

[0081] The module analyzing the difficulty level of hot technologies determines the number of publications corresponding to each hot technology in each year within the preset time period. It then combines this with the weighting of the technology research and development trend impact factor for each year to determine the publication volume trend of the hot technology within the preset time period. Based on this publication volume trend, it determines the technological complexity of the hot technology.

[0082]

[0083] Ns m This refers to the trend of the number of articles published on the m-th trending technology within the preset time period, where the preset time period corresponds to X years, x = 1, 2, 3, ..., X. Let m be the number of publications corresponding to the m-th hot technology in year x. The weight of the technological research and development trend influence factor for the m-th hot technology in year x is set based on the overall development trend of the technological field in which the m-th hot technology is located and the expert judgment value, satisfying the following conditions. and

[0084] The technical complexity is as follows:

[0085]

[0086] Among them, Sd m Let Ns be the technical complexity of the m-th hot technology. max This represents the maximum number of articles published on all trending technologies over the past X years.

[0087] Furthermore, the hotspot technology merging and sorting module performs the following operations for each hotspot technology:

[0088] calculate

[0089] S m,m′ Let λ be the comprehensive correlation influence value of the m-th hot technology relative to the m′-th hot technology. m,m′ μ m,m′ and ν m,m′Let be the weight parameters, and satisfy λ. m,m′ +μ m,m′ +ν m,m′ =1;

[0090] Calculate S m,m′ The corresponding mean and variance, and then S m,m′ Standardize the data:

[0091]

[0092]

[0093] The S m,m′ Data standardization includes: calculation S m,m′ Assigned value in, For S m,m′ The corresponding mean, Sq m The corresponding variance;

[0094] Calculate the covariance matrix of the standardized results:

[0095]

[0096] Among them, cov(S m ,S m′ )=E(S m S m′ )-E(S m E(S) m′ E(·) is the mean function, and S m =[S m,1 ,S m,2 ,S m,3 ,...,S m,M ], S m' =[S m',1 ,S m',2 ,S m',3 ,...,S m',M ], S m In the middle, S m,m =1; S m' In the middle, S m',m' =1;

[0097] Solve the characteristic equation |λ m IC|=0, thus obtaining the eigenvalue λ m , where I is the identity matrix.

[0098] Furthermore, after obtaining the eigenvalues ​​corresponding to each hot technology, the eigenvalues ​​are arranged in descending order, and the sorting result is denoted as the sorted sequence {λ1',λ2',...,λ'}.M} Calculate the feature vector e' corresponding to each element in the sorted sequence. m , satisfying ||e' m || = 1;

[0099] Calculate the contribution rate of each element in the sorted sequence:

[0100]

[0101] Obtain the hotspot technologies corresponding to elements with a contribution rate greater than 0.9 in the sorted sequence, and then extract the feature vector e' corresponding to all the hotspot technologies. m In the process, select the feature vector e' m Hot technologies whose components are all positive are considered hot technologies that meet the first preset condition. These hot technologies are then merged into a technology group, and all hot technologies in the technology group are sorted from largest to smallest according to their comprehensive correlation impact value.

[0102] The information resource database of this invention provides a document data interface for hot technology analysis; the hot technology keyword extraction module is a set of programs with text query, extraction and processing capabilities, used to query keywords of the technical field to be argued from the information resource database, and merge similar keywords based on text similarity, grouping them into the same name, and establishing a mapping relationship between keywords, document resources and their respective hot technologies; the hot technology correlation analysis module is a set of correlation analysis calculation programs, used to calculate the correlation degree between various hot technologies, calculating the correlation score by the number of identical keywords between a certain hot technology and other hot technologies; the hot technology importance analysis module is a set of document analysis programs, used to calculate the importance of document resources in the hot technology field over a period of time. The invention employs a weighted total of impact factors and citation data to characterize the comprehensive academic impact value of a hot technology field. This comprehensive academic impact value is then processed to assign a score indicating the importance of the hot technology. A hot technology difficulty analysis module, a set of statistical procedures, is used to statistically analyze the trend of the number of publications in various years over a period of time. This trend is used to determine the maturity of the hot technology and assign a score indicating its difficulty. A hot technology merging and ranking module, a set of statistical calculation procedures, is used to assign weights to the relevance, importance, and difficulty of hot technologies according to development needs. Based on these weights, a weighted comprehensive analysis is performed, grouping related technologies into technology groups and ranking them according to their importance and difficulty. This invention provides a hot technology development layout analysis method for technology development layout analysis based on a hot technology analysis system, supporting the drawing and generation of hot technology development roadmaps. This invention uses methods based on mathematical statistics and bibliometric analysis to analyze hot technology development plans, and is particularly suitable for assisting decision-making in the demonstration of hot technology development layout during the formulation of science and technology development roadmaps.

[0103] In this invention, literature resources related to the hot technical fields that need to be demonstrated are stored by importing them, while also supporting access to authoritative scientific and technological literature databases, providing a literature data interface for the analysis of hot technologies.

[0104] The hot technology keyword extraction module can perform text query, extraction and processing. It is used to query keywords of the technical field to be demonstrated from the intelligence resource database, merge similar keywords based on text similarity, group them into the same name, and establish a mapping relationship between keywords, literature resources and their respective hot technologies.

[0105] The Hot Technology Correlation Analysis Module is a collection of correlation analysis and calculation programs used to calculate the correlation between various hot technologies. It calculates the correlation score by the number of identical keywords between a hot technology and other hot technologies.

[0106] The Hot Technology Importance Analysis Module is a collection of literature analysis programs used to calculate the impact factor and weighted total amount of citations of literature in hot technology fields over a period of time, representing the comprehensive academic impact value of the hot technology field, and processing the comprehensive academic impact value to give a score of the importance of the hot technology.

[0107] The Hot Technology Difficulty Analysis Module is a collection of literature statistics programs used to statistically analyze the trend of the number of publications of literature resources in each year over a period of time, determine the maturity of the hot technology based on the trend, and give a score for the difficulty of the hot technology.

[0108] The hot technology merging and ranking module is a set of calculation and statistical programs used to assign weights to the relevance, importance, and difficulty of hot technologies according to development needs. Based on the weight coefficients, a weighted comprehensive analysis is performed to group related technologies into technology groups and rank them according to their importance and difficulty in the development layout of the technologies.

[0109] In this invention, λ m,m′ μ m,m′ and ν m,m′ These are weighting parameters, which can be determined based on the needs demonstrated by the technology development roadmap, and set according to the influence of the correlation, importance, and difficulty between two hot technologies on the technology layout, or obtained by fitting after expert judgment, satisfying λ. m,m′ +μ m,m′ +ν m,m′ =1.

[0110] In this invention, the feature vector corresponding to the feature value reaching 90% is characterized by a positive component, which indicates that the corresponding hot technology has a positive impact on the overall score. In other words, hot technologies with positive feature vector components are highly correlated under the constraints of importance and difficulty. According to the extracted feature vector, the hot technologies corresponding to the positive components are regarded as related technology groups and grouped together. The development layout of technologies within the technology group is sorted according to the size of the given comprehensive correlation influence value.

[0111] This invention provides a method for analyzing hot technologies, based on the hot technology analysis system described above, the method comprising:

[0112] Step S1: Obtain literature on the technical field to be demonstrated and store it in the intelligence resource database of the hotspot analysis system;

[0113] Step S2: The hotspot analysis system performs hotspot analysis on the literature of the technical field to be demonstrated, and obtains a technology group;

[0114] Step S3: Based on the technology group, determine the technical route in this technical field.

[0115] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein, and such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A hotspot technology analysis system, characterized by, The system comprises: An intelligence resource database for storing a plurality of literatures to be analyzed for hot technology; the hot technology is a plurality of; A hot technology keyword extraction module for extracting a plurality of keywords related to the hot technology from the literatures, normalizing the keywords based on text similarity, and establishing a mapping relationship among the keywords, the literatures, and the hot technology; the normalization refers to retaining only one keyword for a plurality of keywords with a text similarity greater than a first preset threshold, and replacing the other unretained keywords with the retained keyword; A hot technology correlation degree analysis module for constructing a feature vector corresponding to each hot technology, the feature vector being composed of all keywords corresponding to the hot technology; for each hot technology, a correlation value between the hot technology and other hot technologies is determined based on the similarity between the feature vector corresponding to the hot technology and the feature vectors corresponding to the other hot technologies, the correlation value representing the similarity between the hot technology and the other hot technologies; A hot technology importance analysis module for obtaining all literatures corresponding to each hot technology; for each hot technology, an academic influence value of the hot technology is determined based on the impact factor and citation data of all literatures corresponding to the hot technology within a preset time period; A hot technology difficulty analysis module for determining, for each hot technology, the number of literatures corresponding to the hot technology in each year within the preset time period, determining the number of publications of the hot technology within the preset time period in combination with the technical research and development trend influence factor weight corresponding to each year, and determining the technical complexity of the hot technology based on the number of publications; A hot technology merging and sorting module for determining, for each hot technology, a comprehensive correlation influence value of the hot technology relative to other technology hot spots based on the correlation value, the academic influence value, and the technical complexity; merging hot technologies meeting a first preset condition into the same technology group, and sorting the hot technologies in the same technology group; The hot technology merging and sorting module performs the following operations for each hot technology: Calculate the comprehensive correlation influence value S of the mth hotspot technology relative to the m'th hotspot technology m,m′ ; Calculate S m,m′ The corresponding mean, variance, and S m,m′ Data standardization; Calculating the covariance matrix of the normalized results; Solving the eigen equation |λ m I - C = 0, to obtain the eigenvalue λ m where I is the identity matrix; After the characteristic values corresponding to each hotspot technology are obtained, the characteristic values are arranged in descending order to obtain a ranking sequence, and a characteristic vector e' corresponding to each element in the ranking sequence is calculated m , satisfying ||e' m || = 1. Calculating the contribution rate corresponding to each element in the sorting sequence; acquire hot technologies corresponding to elements with a contribution rate greater than 0.9 in the sorting sequence, and then acquire feature vectors e' corresponding to all acquired hot technologies m In the embodiment, hot technologies with positive values of each component of the feature vector e' m are selected as hot technologies meeting the first preset condition, and the hot technologies meeting the first preset condition are merged into a technology group, and all hot technologies in the technology group are sorted in descending order according to the comprehensive correlation influence values.

2. The system of claim 1, wherein, For each hot technology, a correlation value between the hot technology and other hot technologies is determined based on the similarity between the feature vector corresponding to the hot technology and the feature vectors corresponding to the other hot technologies, the correlation value representing the similarity between the hot technology and the other hot technologies, wherein the calculation formula of the correlation value between the hot technology and the other hot technologies is: wherein, Sr m,m′ is the association value between the mth hot technology and the m'th hot technology, N m,m′ is the number of same keywords between the mth hot technology and the m'th hot technology, N m′ is the number of keywords of the m'th hot technology, N m is the number of keywords of the mth hot technology, 1≤m,m'≤M, and m≠m'.

3. The system of claim 2, wherein, The hot technology importance analysis module obtains all literatures corresponding to each hot technology; for each hot technology, an academic influence value of the hot technology is determined based on the impact factor and citation data of all literatures corresponding to the hot technology within a preset time period, wherein: Is m the academic influence degree of the mth hotspot technology, the impact factor of the lth paper corresponding to the mth hotspot technology m , the number of citations of the lth paper corresponding to the mth hotspot technology m , l m = 1,2,3,...,L m , L m is the total number of literature corresponding to the mth hotspot technology; The academic influence value of the hot technology is determined, and the calculation formula is: wherein Si m is the academic impact value of the mth hotspot technology, Is max is the maximum value of the academic impact of all hotspot technologies.

4. The system of claim 3, wherein, The hotspot technology difficulty analysis module determines the number of literatures corresponding to each hotspot technology in each year within the preset time period, determines the number of papers of the hotspot technology within the preset time period in combination with the technical research development trend influence factor weight corresponding to each year, determines the technical complexity of the hotspot technology based on the number of papers, and wherein: Ns m is the number of the mth hot technology in the preset time period, and the preset time period corresponds to X years, x = 1, 2, 3,..., X, is the number of the mth hot technology in the xth year, is the technology research and development trend influence factor weight of the mth hot technology in the xth year, the technology research and development trend influence factor weight is fitted and set according to the overall development trend of the technical field where the mth hot technology is located and the expert judgment value, and satisfies and The technical complexity is: Where, Sd m is the technology complexity of the mth hotspot technology, Ns max is the maximum value of the number of publications trend of the past X years of all hotspot technologies.

5. The system of claim 4, wherein, Calculate the comprehensive correlation influence value S of the mth hotspot technology relative to the m'th hotspot technology m,m′ ; calculate S m,m′ The corresponding mean, variance, and specific as follows: Computing S m,m′ is the comprehensive correlation influence value of the mth hotspot technology relative to the m'th hotspot technology, λ m,m′ , μ m,m′ and ν m,m′ are weight parameters, and satisfy λ m,m′ + μ m,m′ + ν m,m′ = 1; The S m,m′ Data standardization includes: calculation S m,m′ Assigned value in, For S m,m′ The corresponding mean, Sq m The corresponding variance; The covariance matrix of the standardized results is calculated, specifically: cov(S m ,S m′ ) = E(S m S m′ ) - E(S m )E(S m′ ), E(·) is a mean function, S m = [S m,1 , S m,2 , S m,3 ,..., S m,M ], S m' = [S m',1 , S m',2 , S m',3 ,..., S m',M ], S m , in which S m,m = 1; S m' , in which S m',m' = 1.

6. The system of claim 5, wherein, The ordering sequence is represented as {λ'1', λ'2,..., λ' M}; The contribution rate corresponding to each element in the sorting sequence is calculated, specifically:

7. A hotspot technology analysis method based on the hotspot technology analysis system according to any one of claims 1-6, characterized in that, The method comprises: Step S1: obtaining the literature of the technical field to be demonstrated and storing it in the intelligence resource database of the hotspot analysis system; Step S2: the hotspot analysis system performs hotspot analysis on the literature of the technical field to be demonstrated to obtain a technology group; Step S3: determining the technical route of the technical field based on the technology group.

8. An electronic device, the device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method of claim 7.

9. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of claim 7.

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