A data trend analysis method and apparatus

Abstract

The application relates to the technical field of data processing, and discloses a data trend analysis method and device, which comprises the following steps: receiving a target technical field to be analyzed; performing pre-retrieval processing based on the target technical field to generate an expanded technology list, wherein the expanded technology list comprises a plurality of technical points consistent with the technical direction of the target technical field; and performing focused retrieval of a specified range and a specified direction based on the expanded technology list to obtain a target retrieval result of the target technical field in the specified range and the specified direction, wherein the specified range is used for representing the data range of retrieval, and the specified direction is used for representing the attention direction selected from the plurality of technical points. Therefore, the reliability of trend analysis of the target technical field is significantly improved, and the obtained trend analysis result has a wider application prospect.

Description

Technical Field

[0001] This invention relates to the field of natural language understanding technology, specifically to a data trend analysis method and apparatus. Background Technology

[0002] Technology trend analysis is crucial for corporate decision-making and research direction selection, and numerous automated methods for analyzing technology trends already exist. For example, automated scripts can periodically acquire economic information datasets, preprocess them, perform feature selection using a wrapper feature selection method, conduct data mining based on decision tree algorithms to obtain classification results, and finally use statistical analysis and data visualization to obtain visualized economic information. However, data acquired through automated scripts cannot guarantee data quality, leading to poor reliability of analysis results from the data source. Furthermore, the depth and breadth of trend analysis are relatively limited, and the analysis results cannot be directly obtained, potentially failing to comprehensively address the complex and ever-changing trends in the technology field. To address this, some technologies involve targeted searches of literature reports within a specific technology field, utilizing the clustering functions of specific tools to analyze the retrieved literature, thereby obtaining relatively objective technology trend analysis reports for that specific field. However, such solutions are typically limited to a relatively single search scope and analysis dimension, resulting in significant limitations in the analysis results. Summary of the Invention

[0003] In view of this, the present invention provides a data trend analysis method and apparatus to solve or partially solve the problem of significant limitations in the analysis results during the data analysis process.

[0004] In a first aspect, the present invention provides a data trend analysis method, the method comprising:

[0005] Receive the target technical field to be analyzed;

[0006] Pre-search processing is performed based on the target technology field to generate an expanded technology list, which includes multiple technology points that are consistent with the technology direction of the target technology field.

[0007] Based on the expanded technology list, a focused search is performed within a specified range and in a specified direction to obtain target search results in the target technology field within the specified range and in the specified direction. The specified range is used to characterize the data range of the search, and the specified direction is used to characterize the focus selected from multiple technology points.

[0008] By performing time-series processing and information extraction and integration based on the target retrieval results, trend analysis results in the target technology field are obtained.

[0009] This invention's data trend analysis method, upon receiving a user-inputted target technology field for analysis, first performs a pre-search based on the target technology field to generate an expanded technology list. Then, based on this expanded technology list, it performs a focused search within the specified scope and direction, obtaining target search results for the target technology field within the specified scope and direction. Finally, based on these search results, it performs time-series processing and information extraction and integration to obtain trend analysis results for the target technology field. Thus, by pre-searching the target technology field to obtain an expanded technology list, it ensures an accurate grasp of the target technology field, identifying multiple technology points consistent with the target technology field's technical direction. Based on this expanded technology list, it selects more accurate technology-specific directions, enabling more targeted retrieval and information extraction and integration in subsequent focused searches, resulting in more accurate trend analysis results for the target technology field. This significantly improves the reliability of trend analysis for the target technology field, making the obtained trend analysis results have broader application prospects.

[0010] In some optional implementations, pre-search processing is performed based on the target technical field, including:

[0011] Use search engines to search for relevant information in the target technology field;

[0012] Based on the associated information, analysis and processing instructions for the target technical field are generated. The analysis and processing instructions include the technical points extracted from the associated information and the processing methods for the technical points.

[0013] Based on analysis and processing instructions, related information is extracted and classified.

[0014] This invention provides a data trend analysis method that utilizes a search engine to retrieve relevant information within a target technology field. This information is then extracted and categorized using analysis and processing instructions to generate an expanded technology list that includes multiple technical points aligned with the target technology field. This effectively achieves a comprehensive understanding of the target technology field, ensuring that trend analysis is based on complete and reliable data.

[0015] In some alternative implementations, a search engine is used to retrieve relevant information in the target technical field, including:

[0016] Based on search engines, keywords in the target technology field are expanded to obtain extended keywords;

[0017] Perform a search based on expanded keywords to obtain search results;

[0018] The search results are filtered to obtain relevant information that meets the set requirements for relevance to the target technology field.

[0019] This invention provides a data trend analysis method based on a search engine. It expands the target technology field with keywords and performs a search based on these expanded keywords. The method then filters the search results to obtain relevant information that meets predefined requirements for relevance to the target technology field. This effectively expands the data scope used for analyzing the target technology field and ensures the relevance of the retrieved data to the target technology field, thereby guaranteeing the effectiveness of the subsequent trend analysis results.

[0020] In some optional implementations, based on the associated information, analysis and processing instructions for the target technical field are generated, including:

[0021] Extract key information from related information;

[0022] Based on the set key information and preset command rules, analysis and processing instructions are generated.

[0023] In some optional implementations, the specified scope refers to the data range of the defined search engine; focused retrieval based on an expanded list of technologies within the specified scope and direction includes:

[0024] Receive in the specified direction selected based on the extended technology list;

[0025] Based on the configured search engine, a primary focused search is performed in the specified direction.

[0026] The data trend analysis method of this invention can receive a specified direction selected by the user based on an expanded technology list, and perform a first focused search on the specified direction by setting a search engine. Thus, after obtaining the target search results by pre-searching the target technology field, further targeted search based on the user-specified direction can be achieved, which can effectively improve information processing efficiency and ensure the validity and accuracy of information, and significantly improve the user experience.

[0027] In some optional implementations, the specified scope is defined as a specialized database; focused retrieval based on an expanded technology list within a specified scope and direction includes:

[0028] Receive in the specified direction selected based on the extended technology list;

[0029] A second focused search is performed on a specified direction based on a designated professional database.

[0030] The data trend analysis method of this invention can receive a specified direction selected by the user based on an expanded technology list, and perform a second focused search on the specified direction by setting up a professional database. Thus, after obtaining the target search results through pre-search processing of the target technology field, the method can achieve targeted search based on the user-specified direction by using a professional database, which effectively improves information processing efficiency and ensures the validity and accuracy of information from the source, significantly improving the user experience.

[0031] In some alternative implementations, the method further includes, prior to time-series processing and information extraction and integration based on the target retrieval results:

[0032] Filter the target search results for data that meets the set time range, whose relevance to multiple technical points meets the set relevance threshold range, and whose data source meets the set data source range;

[0033] Update the target search results based on the filtering results.

[0034] The data trend analysis method of this invention filters data from the target retrieval results before performing time-series processing and information extraction and integration based on the target retrieval results. This filters data that meets the set time range, whose correlation with multiple technical points meets the set correlation threshold range, and whose data source meets the set data source range. Thus, during the information processing process, data that meets the user's needs is continuously filtered, effectively ensuring the accuracy of data information at each stage of data processing and avoiding redundant information from entering the next operation step. This ensures the accuracy and authority of the final data trend analysis results.

[0035] In some optional implementations, time-series processing and information extraction and integration are performed based on the target retrieval results, including:

[0036] The search results for the target are processed over time to obtain academic trend analysis results that characterize the technological development and change trends in the target technology field and the popularity of multiple technical points.

[0037] The data trend analysis method of this invention, by performing time-series processing on the target retrieval results, obtains academic trend analysis results that characterize the technological development and change trends of the target technology field and the popularity of multiple technical points. It provides academic trend analysis results that characterize the technological development and change trends of the target technology field and the popularity of multiple technical points in a very intuitive time-series expression, which is more conducive to users conducting efficient and accurate analysis and research based on academic trend analysis results.

[0038] In some optional implementations, the temporal processing and information extraction and integration based on the target retrieval results also include:

[0039] Based on the target retrieval results and academic trend analysis results, generate instructions for analyzing technology development trends;

[0040] In response to the command for analyzing technology development trends, the system performs pre-set information extraction and integration corresponding to the type of technology development trend to obtain the results of the technology development trend analysis.

[0041] Among them, the technology development trend analysis command carries the type of technology development trend.

[0042] The data trend analysis method of this invention also generates technology development trend analysis instructions based on target retrieval results and academic trend analysis results. In response to these instructions, it performs pre-set information extraction and integration corresponding to the technology development trend type to obtain the technology development trend analysis results. This fully demonstrates high flexibility and user-friendliness.

[0043] Secondly, the present invention also provides a data trend analysis device, the device comprising:

[0044] The receiving module is used to receive the target technical field to be analyzed;

[0045] The extension module is used to perform pre-search processing based on the target technology field and generate an expanded technology list, which includes multiple technology points that are consistent with the technology direction of the target technology field.

[0046] The retrieval module is used to perform focused retrieval within a specified range and direction based on an expanded technology list, and to obtain target retrieval results in the target technology field within the specified range and direction. The specified range is used to characterize the data range of the retrieval, and the specified direction is used to characterize the focus selected from multiple technology points.

[0047] The information integration module is used to perform time-series processing and information extraction and integration based on the target retrieval results to obtain trend analysis results in the target technology field.

[0048] This invention's data trend analysis method, upon receiving a user-inputted target technology field for analysis, first performs a pre-search based on the target technology field to generate an expanded technology list. Then, based on this expanded technology list, it performs a focused search within the specified scope and direction, obtaining target search results for the target technology field within the specified scope and direction. Finally, based on these search results, it performs time-series processing and information extraction and integration to obtain trend analysis results for the target technology field. Thus, by pre-searching the target technology field to obtain an expanded technology list, it ensures an accurate grasp of the target technology field, identifying multiple technology points consistent with the target technology field's technical direction. Based on this expanded technology list, it selects more accurate technology-specific directions, enabling more targeted retrieval and information extraction and integration in subsequent focused searches, resulting in more accurate trend analysis results for the target technology field. This significantly improves the reliability of trend analysis for the target technology field, making the obtained trend analysis results have broader application prospects. Attached Figure Description

[0049] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0050] Figure 1 This is a flowchart illustrating a data trend analysis method according to an embodiment of the present invention;

[0051] Figure 2 This is a flowchart illustrating another data trend analysis method according to an embodiment of the present invention;

[0052] Figure 3 This is a flowchart illustrating a specific application example of the data trend analysis method according to an embodiment of the present invention;

[0053] Figure 4 This is a structural block diagram of a data trend analysis device according to an embodiment of the present invention;

[0054] Figure 5 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0056] This invention provides a data trend analysis method and apparatus, aiming to address the limitations of existing technology trend analysis methods in related technologies. Specifically, existing technology trend analyses either focus on specific fields or data types, or are insufficient in terms of depth, breadth, and timeliness, and none of them can meet users' needs for comprehensive, accurate, and timely analysis of rapidly changing and complex technology trends.

[0057] To address or partially address the limitations of analytical results in the aforementioned data analysis process, this invention proposes a data trend analysis method and apparatus. This method, based on a large-scale model, enables technology trend analysis by integrating multi-source data such as patents, academic literature, industry reports, and news information. Leveraging the powerful semantic understanding and knowledge generation capabilities of the large-scale model, it conducts multi-dimensional and in-depth mining and prediction of technology trends, providing decision-makers with more comprehensive, accurate, and timely insights into technology trends. Specifically, the received target technology field or technology point to be analyzed undergoes pre-retrieval processing to expand the technology points, resulting in an expanded technology list including multiple technology points. Users can specify a direction based on this expanded technology list, thereby conducting a more comprehensive and targeted search based on that direction to obtain more accurate target search results. This allows for detailed and accurate analysis based on the target search results, achieving technology trend analysis consistent with the target technology field or technology point.

[0058] According to an embodiment of the present invention, a data trend analysis method embodiment is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0059] This embodiment provides a data trend analysis method, which can be used in computer equipment, etc. Figure 1 This is a flowchart illustrating a data trend analysis method according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps:

[0060] In a first aspect, the present invention provides a data trend analysis method, the method comprising:

[0061] Step S101: Receive the target technical field to be analyzed.

[0062] Specifically, the technical field can be a relatively broad technical direction, while the technical point can be a relatively specific technical direction.

[0063] For example, a GUI (Graphical User Interface) can be pre-configured for users to input or select target technology areas. Industry experts and other users can use the GUI to select or input specific target technology areas for technology trend analysis, such as "spatial computing".

[0064] Step S102: Perform pre-search processing based on the target technology field to generate an expanded technology list, which includes multiple technology points that are consistent with the technology direction of the target technology field.

[0065] Specifically, the purpose of pre-search processing of the target technology field is to expand the keywords of the target technology field entered by the user, thereby ensuring the integrity of the data used in the trend analysis of the target technology field.

[0066] Here, we can first use search engines and established databases to conduct searches, and then use NLP (National Language Processing) technology to extract and organize information such as technical terms, algorithm names, and application scenarios from the retrieved content, thereby generating an expanded technology list.

[0067] Step S103: Based on the expanded technology list, perform a focused search within a specified range and in a specified direction to obtain target search results in the target technology field within the specified range and in the specified direction. The specified range is used to characterize the data range of the search, and the specified direction is used to characterize the focus selected from multiple technology points.

[0068] Specifically, this section allows users to select a specific scope or technical direction based on the expanded technology list. The specified scope mainly refers to the data source or retrieval method, such as a professional academic paper database or using a specific search engine. The specified direction mainly refers to the technical points selected from the expanded technology list.

[0069] For a specified range, the search can be performed based on the academic database or search engine selected by the user. If the user does not input any information, or if the user can specify a first set number of databases or a second set number of search engines, but the number of databases specified by the user is less than the first set number or the number of search engines specified by the user is less than the second set number, the search can be performed based on the default database and the default search engine.

[0070] Furthermore, the system can also receive specified technical directions selected by the user from the expanded technology list. If the user does not input any information, or if the number of specified technical directions selected by the user is less than a third preset number, the system can also determine the similarity and relevance information between multiple technical points in the expanded technology list and the target technology field. After determining the similarity and relevance information between multiple technical points in the expanded technology list and the target technology field, the system selects the technical points ranked in the top preset positions according to the similarity or relevance from high to low as the specified directions for focused retrieval. The methods for determining similarity and relevance can be determined according to actual needs; for example, semantic analysis can be used to obtain the similarity and relevance between multiple technical points in the expanded technology list and the target technology field.

[0071] Therefore, by performing focused searches within a specified range and direction based on the expanded technology list, target search results in the target technology field are obtained within the specified range and direction. The specified range is used to characterize the data range of the search, and the specified direction is used to characterize the focus selected from multiple technology points.

[0072] Step S104: Based on the target retrieval results, perform time-series processing and information extraction and integration to obtain trend analysis results in the target technology field.

[0073] Specifically, time-series analysis can be performed on information such as papers or patents in the target search results to identify academic trends in the technological development of the target technology field, such as the annual frequency of occurrence of technical points and changes in research popularity. For example, time-series charts can be generated to visually display academic trends in technological development.

[0074] Furthermore, one can also use industry reports and news content retrieved through search engines to determine the application status of technologies, including theoretical research, product prototypes, and technical prototypes, and combine this with academic trends in technology development to form technology trend analysis commands. For example, this could include the development trend of a technology, potential application areas, and possible technological breakthroughs.

[0075] This invention's data trend analysis method, upon receiving a user-inputted target technology field for analysis, first performs a pre-search based on the target technology field to generate an expanded technology list. Then, based on this expanded technology list, it performs a focused search within the specified scope and direction, obtaining target search results for the target technology field within the specified scope and direction. Finally, based on these search results, it performs time-series processing and information extraction and integration to obtain trend analysis results for the target technology field. Thus, by pre-searching the target technology field to obtain an expanded technology list, it ensures an accurate grasp of the target technology field, identifying multiple technology points consistent with the target technology field's technical direction. Based on this expanded technology list, it selects more accurate technology-specific directions, enabling more targeted retrieval and information extraction and integration in subsequent focused searches, resulting in more accurate trend analysis results for the target technology field. This significantly improves the reliability of trend analysis for the target technology field, making the obtained trend analysis results have broader application prospects.

[0076] This embodiment provides a data trend analysis method, which can be used in computer equipment, etc. Figure 2 This is a flowchart illustrating another data trend analysis method according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps:

[0077] Step S201: Receive the target technical field to be analyzed.

[0078] Please see details Figure 1 Step S101 of the illustrated embodiment will not be described again here.

[0079] Step S202: Perform pre-search processing based on the target technology field to generate an expanded technology list, which includes multiple technology points that are consistent with the technology direction of the target technology field.

[0080] Specifically, step S202 may include:

[0081] Step S2021: Use a search engine to search for relevant information in the target technical field.

[0082] In some alternative implementations, step S2021 may include:

[0083] Step a1: Based on the search engine, expand the keywords of the target technology field to obtain expanded keywords.

[0084] Specifically, you can configure search engine parameters to initially expand keywords related to the target technology field. For example, if the target technology field is "spatial computing," you can use semantic analysis to initially expand keywords such as "spatial computing," "3D modeling," "virtual reality," and "augmented reality."

[0085] Step a2: Perform a search operation based on the expanded keywords to obtain the search results.

[0086] Specifically, searches can be performed based on expanded keywords. The search scope can include academic databases such as IEEE Xplore (digital library) and PubMed (biomedical literature database), as well as patent databases such as Google Patents and USPTO (United States Patent and Trademark Office), technical forums, industry reports, etc. It should be noted that the use of databases and data sources mentioned here and in other descriptions complies with relevant laws and regulations.

[0087] Step a3: Filter the search results to obtain relevant information that meets the set requirements for relevance to the target technology field.

[0088] Specifically, search results can be scientific literature or web pages related to industry news in the target technology field. After obtaining the search results, parameters representing the relevance of the search results to the target technology field can be obtained through calculations such as similarity and relevance. Based on this, the search results are filtered to exclude those with low relevance to the target technology field, resulting in relevant information whose relevance to the target technology field meets the set requirements. For example, similarity calculations can be used to exclude scientific literature or web page content with a similarity lower than a set similarity threshold to "spatial computing".

[0089] This invention provides a data trend analysis method based on a search engine. It expands the target technology field with keywords and performs a search based on these expanded keywords. The method then filters the search results to obtain relevant information that meets predefined requirements for relevance to the target technology field. This effectively expands the data scope used for analyzing the target technology field and ensures the relevance of the retrieved data to the target technology field, thereby guaranteeing the effectiveness of the subsequent trend analysis results.

[0090] Step S2022: Based on the associated information, generate analysis and processing instructions for the target technical field. The analysis and processing instructions include the technical points extracted from the associated information and the processing methods for the technical points.

[0091] In some alternative implementations, step S2022 may include:

[0092] Step b1: Extract key information from the associated information.

[0093] Specifically, key information can be literature or web page content that meets the set requirements for relevance to the target technical field. Here, NLP (National Language Processing) technology can be used to extract key information such as technical points, application areas, and related technologies from the literature or web page content.

[0094] Step b2: Based on the set key information and preset command rules, generate analysis and processing instructions.

[0095] The preset command rules here can be predefined sentence structures, such as: "Based on the extraction of key information from related information, please analyze from a spatiotemporal perspective what new technical points exist in the [target technical field]." The [target technical field] can reference content from a specified location.

[0096] Therefore, by extracting key information from related information, analysis and processing commands can be generated, such as "Based on the key information extracted by the system, please analyze from a spatiotemporal perspective what new technical points exist in the field of spatial computing." These analysis and processing commands can be used to guide large models in more in-depth analysis, such as extracting and classifying related information.

[0097] Step S2023: Based on the analysis and processing instructions, extract and classify the related information.

[0098] Here, a pre-trained large model can be used to extract and classify the related information. After receiving the analysis and processing instructions, the large model can extract the extended technical points related to the target technical field from the related information.

[0099] Specifically, large models can use natural language processing technology to identify and extract technical terms, algorithm names, application scenarios, etc. from related information based on analysis and processing instructions, and then classify and organize the extracted information.

[0100] For example, new technologies extracted from a large model can be compiled into an expanded technology list. Each entry in the expanded technology list includes the name of the technology, the number of relevant publications for that technology, and its main application areas. The information in the expanded technology list can be configured and processed according to actual needs. The expanded technology list can be configured to allow users to sort, filter, and export the information in the list, enabling users to conduct further analysis based on their specific requirements.

[0101] This invention provides a data trend analysis method that utilizes a search engine to retrieve relevant information within a target technology field. This information is then extracted and categorized using analysis and processing instructions to generate an expanded technology list that includes multiple technical points aligned with the target technology field. This effectively achieves a comprehensive understanding of the target technology field, ensuring that trend analysis is based on complete and reliable data.

[0102] For other specific implementation details, please refer to Figure 1 Step S102 of the illustrated embodiment will not be described again here.

[0103] Step S203: Based on the expanded technology list, perform a focused search within a specified range and in a specified direction to obtain target search results in the target technology field within the specified range and in the specified direction. The specified range is used to characterize the data range of the search, and the specified direction is used to characterize the focus selected from multiple technology points.

[0104] Specifically, step S203 may include:

[0105] Step c1: Receive the specified direction selected based on the extended technology list.

[0106] In some optional implementations, the specified direction can refer to a technical point selected from the expanded technology list. Selecting a specified direction allows you to obtain information from the expanded technology list, such as the name of the technical point included in the corresponding entry, the number of relevant documents for that technical point, and the main application areas of that technical point.

[0107] Step c2: Perform a first focused search in the specified direction based on the set search engine.

[0108] Here, searches can be performed based on the search engine selected by the user. If the user does not input any information, or if a second set number of search engines can be specified by default, but the number of databases specified by the user is less than the number of search engines specified by the user, which is less than the second set number, then the default search engine can be used for the search.

[0109] The data trend analysis method of this invention can receive a specified direction selected by the user based on an expanded technology list, and perform a first focused search on the specified direction by setting a search engine. Thus, after obtaining the target search results by pre-searching the target technology field, further targeted search based on the user-specified direction can be achieved, which can effectively improve information processing efficiency and ensure the validity and accuracy of information, and significantly improve the user experience.

[0110] In some alternative implementations, step S203 may include:

[0111] Step d1: Receive the specified direction selected based on the extended technology list.

[0112] For details, please refer to step c1 above, which will not be repeated here.

[0113] Step d2 involves performing a second focused search on the specified direction based on the established professional database.

[0114] This can be based on academic databases selected by the user. If the user does not input any information, or if the user can specify a first set number of databases for searching, but the number of databases specified by the user is less than the first set number, then the search can be based on the default databases.

[0115] Here, other methods can also be used for focused retrieval, and all the content obtained from focused retrieval is summarized to obtain the target retrieval results.

[0116] The data trend analysis method of this invention can receive a specified direction selected by the user based on an expanded technology list, and perform a second focused search on the specified direction by setting up a professional database. Thus, after obtaining the target search results through pre-search processing of the target technology field, the method can achieve targeted search based on the user-specified direction by using a professional database, which effectively improves information processing efficiency and ensures the validity and accuracy of information from the source, significantly improving the user experience.

[0117] For other specific implementation details, please refer to Figure 1 Step S103 of the illustrated embodiment will not be described again here.

[0118] Step S204: Filter the target search results for data that meets the set time range, whose correlation with multiple technical points meets the set correlation threshold range, and whose data source meets the set data source range.

[0119] Specifically, the target search results contain some noise, such as: relatively early, sporadic, and unformed journal articles retrieved when analyzing the development trends of cutting-edge technologies, as well as papers published in journals or conferences with impact factors lower than the set impact threshold, and patents applied for earlier than the set time but not yet granted.

[0120] Therefore, a pre-trained information quality control model that assesses the information quality of the retrieved target search results can be used to evaluate the information quality. This quality assessment can include the accuracy, timeliness, relevance, and authority of the information in the target search results.

[0121] For accuracy evaluation, a judgment model can be trained in advance using high-value text data samples to judge the contextual relevance and completeness of the content in a document. This judgment model can then be used to judge the completeness of the document content itself and the contextual relevance of the document content included in the target retrieval results, thereby evaluating the accuracy of multiple document contents in the target retrieval results.

[0122] To evaluate timeliness, multiple documents in the target search results can be assigned values ​​based on different time ranges. This allows for subsequent comprehensive evaluation and filtering of documents based on parameters such as accuracy, relevance, and timeliness. Alternatively, documents meeting specific timeliness criteria can be filtered first. For example, only patents with application dates within a set time range, journals or monographs with publication dates within a set time range, and webpage content with publication dates within a set time range can be filtered. Then, documents in the target search results that meet the set timeliness criteria can be evaluated and filtered based on accuracy, relevance, and authority.

[0123] For the evaluation of authority, the authority of multiple documents in the target search results can be evaluated based on factors such as the journal's impact factor, the relevance of the journal type to the target technical field, and the pre-configured journal publishing institution assignment principles.

[0124] For evaluating relevance, NLP technology can be used to assess the relevance of the document content of multiple documents in the target search results to the target technical field.

[0125] The above methods, which consider multiple evaluation dimensions of the target search results, can be used for final evaluation. Alternatively, documents meeting multiple evaluation dimensions can be selected sequentially. Another approach is to first filter multiple documents based on a single evaluation dimension, and then further evaluate and finalize the results using other evaluation dimensions. Furthermore, other applicable evaluation methods can be set according to actual needs.

[0126] Step S205: Update the target search results based on the filtering results.

[0127] By comprehensively evaluating, filtering, and updating the target search results, the reliability of the trend analysis results obtained from processing the target search results is effectively improved.

[0128] The data trend analysis method of this invention filters data from the target retrieval results before performing time-series processing and information extraction and integration based on the target retrieval results. This filters data that meets the set time range, whose correlation with multiple technical points meets the set correlation threshold range, and whose data source meets the set data source range. Thus, during the information processing process, data that meets the user's needs is continuously filtered, effectively ensuring the accuracy of data information at each stage of data processing and avoiding redundant information from entering the next operation step. This ensures the accuracy and authority of the final data trend analysis results.

[0129] Step S206: Based on the target retrieval results, perform time-series processing and information extraction and integration to obtain trend analysis results in the target technology field.

[0130] Specifically, step S206 may include:

[0131] Step S2061: Perform time-series processing on the target retrieval results to obtain academic trend analysis results that characterize the technological development and change trends of the target technology field and the popularity of multiple technical points.

[0132] In some optional implementations, time series analysis can be performed based on information such as the application date, publication date, authorization date, or release date of documents like papers and patents in the target search results to identify academic trends in technological development, such as the annual frequency of technological points and changes in research popularity. Here, time series charts for the target search results can be generated to visually display academic trends in technological development.

[0133] The data trend analysis method of this invention, by performing time-series processing on the target retrieval results, obtains academic trend analysis results that characterize the technological development and change trends of the target technology field and the popularity of multiple technical points. It provides academic trend analysis results that characterize the technological development and change trends of the target technology field and the popularity of multiple technical points in a very intuitive time-series expression, which is more conducive to users conducting efficient and accurate analysis and research based on academic trend analysis results.

[0134] In some alternative implementations, step S206 may further include:

[0135] Step S2062: Based on the target retrieval results and academic trend analysis results, generate a technology development trend analysis instruction.

[0136] Specifically, one can determine the application status of technologies, such as theoretical research, product prototypes, and technical prototypes, based on industry reports and news content in the target search results, and combine this with academic trends in technology development to form a technology trend analysis command. For example, this could include the development trends of the technical points involved in the target search results, the potential application areas of the target technology field shown in the target search results, and the potential technological breakthroughs in the target technology field shown in the target search results.

[0137] Step S2063: In response to the technology development trend analysis instruction, perform the pre-set information extraction and integration corresponding to the technology development trend type to obtain the technology development trend analysis result, wherein the technology development trend analysis instruction carries the technology development trend type.

[0138] Here, users can select one or more technology development trend analysis instructions generated in step S2062 for information extraction and integration. If no technology development trend analysis instruction is received from the user within a set time, the set technology development trend analysis instruction can be executed based on the default configuration. For example, the technology development trend analysis instruction "development trend of technology points involved in the target search results" can be executed first.

[0139] The data trend analysis method of this invention also generates technology development trend analysis instructions based on target retrieval results and academic trend analysis results. In response to these instructions, it performs pre-set information extraction and integration corresponding to the technology development trend type to obtain the technology development trend analysis results. This fully demonstrates high flexibility and user-friendliness.

[0140] For other specific implementation details, please refer to Figure 1 Step S104 of the illustrated embodiment will not be described again here.

[0141] This embodiment provides a data trend analysis method, which can be used in computer equipment, etc. Figure 3 This is a flowchart illustrating a specific application example of the data trend analysis method according to an embodiment of the present invention, such as... Figure 3 As shown, the process includes the following steps:

[0142] Step S301: Receive the target technical field to be analyzed.

[0143] Specifically, it can receive technical fields or technical points specified by users such as experts.

[0144] For other specific implementation details, please refer to Figure 1 Step S101 of the illustrated embodiment will not be described again here.

[0145] Step S302: Perform pre-search processing based on the target technology field to generate an expanded technology list, which includes multiple technology points that are consistent with the technology direction of the target technology field.

[0146] Specifically, step S302 may include:

[0147] In step S3021, the search engine searches for relevant fields or technical points and obtains related information.

[0148] Step S3022: Based on the associated information, generate analysis and processing instructions for the technical points.

[0149] Step S3023: Using a large model, extract multiple extended technical points based on analysis and processing instructions.

[0150] Step S3024: Organize the expanded technology points to obtain an expanded technology list.

[0151] For further details on the implementation of step S302, please refer to [link / reference]. Figure 1 Step S102 of the illustrated embodiment will not be described again here.

[0152] Step S303: Based on the expanded technology list, perform a focused search within a specified range and in a specified direction to obtain target search results in the target technology field within the specified range and in the specified direction. The specified range is used to characterize the data range of the search, and the specified direction is used to characterize the focus selected from multiple technology points.

[0153] Specifically, search engines can be used to retrieve target search results based on the expanded technology list and user needs information. Furthermore, technical information related to multiple technology points in the expanded technology list can be obtained from academic databases.

[0154] Furthermore, a pre-trained information quality control model can be used to filter and update the target retrieval results.

[0155] Please see details Figure 1 Step S103 of the illustrated embodiment will not be described again here.

[0156] Step S304: Based on the target retrieval results, perform time-series processing and information extraction and integration to obtain trend analysis results in the target technology field.

[0157] Specifically, based on the target retrieval results, time-series processing and information extraction and integration are performed to generate time-series analysis results containing information resources from multiple high-quality channels and new technologies, as well as technology development trend analysis instructions containing information on multiple technical fields, technologies, information resources, and time-series analysis results. Furthermore, based on a pre-trained large model and the technology development trend analysis instructions, information is extracted, integrated, and inferred to obtain a development trend map of the technologies.

[0158] Please see details Figure 1 Step S104 of the illustrated embodiment will not be described again here.

[0159] This embodiment also provides a data trend analysis device for implementing the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0160] This embodiment provides a data trend analysis device, such as... Figure 4 As shown, it includes:

[0161] Receiver module 401 is used to receive the target technical field to be analyzed;

[0162] Extension module 402 is used to perform pre-retrieval processing based on the target technology field and generate an expanded technology list, which includes multiple technology points that are consistent with the technology direction of the target technology field.

[0163] The retrieval module 403 is used to perform focused retrieval within a specified range and direction based on an expanded technology list, and to obtain target retrieval results in the target technology field within the specified range and direction. The specified range is used to characterize the data range of the retrieval, and the specified direction is used to characterize the focus direction selected from multiple technology points.

[0164] The information integration module 404 is used to perform time-series processing and information extraction and integration based on the target retrieval results to obtain trend analysis results in the target technology field.

[0165] In some alternative implementations, extension module 402 includes:

[0166] The related retrieval unit is used to retrieve related information by using a search engine to search for information in the target technical field;

[0167] The instruction generation unit is used to generate analysis and processing instructions for the target technical field based on the associated information. The analysis and processing instructions include the technical points extracted from the associated information and the processing methods for the technical points.

[0168] The extraction unit is used to extract and classify related information based on analysis and processing instructions.

[0169] In some optional implementations, the association retrieval unit includes:

[0170] The keyword sub-unit is used to expand keywords in the target technology field based on search engines, thereby obtaining expanded keywords;

[0171] The search sub-unit is used to perform search operations based on expanded keywords and obtain search results;

[0172] The filtering subunit is used to filter relevant information from the search results that meets the set requirements for relevance to the target technical field.

[0173] In some optional implementations, the instruction generation unit includes:

[0174] The key information subunit is used to extract key information from related information.

[0175] The generation subunit is used to generate analysis and processing instructions based on key information and preset command rules.

[0176] In some optional implementations, the specified range is defined as the data range of the search engine; the retrieval module 403 includes:

[0177] The first receiving subunit is used to receive a specified direction selected based on the extended technology list;

[0178] The engine retrieval subunit is used to perform a first focused retrieval in a specified direction based on the set search engine.

[0179] In some optional implementations, the specified scope is defined as a specialized database; focused retrieval based on an expanded technology list within a specified scope and direction includes:

[0180] The second receiving subunit is used to receive a specified direction selected based on the extended technology list;

[0181] The database retrieval subunit is used to perform a second focused retrieval in a specified direction based on a set professional database.

[0182] In some alternative embodiments, the apparatus further includes:

[0183] The data pre-screening module is used to filter data in the target retrieval results that meet the set time range, whose correlation with multiple technical points meets the set correlation threshold range, and whose data source meets the set data source range before performing time-series processing and information extraction and integration based on the target retrieval results.

[0184] The search update module is used to update the target search results based on the filtering results.

[0185] In some alternative implementations, the information integration module 404 includes:

[0186] The time-series integration unit is used to perform time-series processing on the target retrieval results to obtain academic trend analysis results that characterize the technological development and change trends of the target technology field and the popularity of multiple technical points.

[0187] In some alternative implementations, the information integration module 404 further includes:

[0188] The analysis instruction unit is used to generate technology development trend analysis instructions based on the target retrieval results and academic trend analysis results;

[0189] The instruction integration unit is used to respond to the technology development trend analysis instruction, execute the pre-set information extraction and integration corresponding to the type of technology development trend, and obtain the technology development trend analysis result.

[0190] Among them, the technology development trend analysis command carries the type of technology development trend.

[0191] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0192] In this embodiment, the data trend analysis device is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0193] This invention also provides a computer device having the above-described features. Figure 4 The data trend analysis device shown.

[0194] Please see Figure 5 , Figure 5 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 5 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 5 Take a processor 10 as an example.

[0195] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0196] The memory 20 stores instructions executable by at least one processor 10 to cause at least one processor 10 to perform the method shown in the above embodiments.

[0197] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0198] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0199] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0200] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0201] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0202] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A data trend analysis method, characterized in that, The method includes: Receive the target technical field to be analyzed; Pre-search processing is performed based on the target technology field to generate an expanded technology list, which includes multiple technology points that are consistent with the technology direction of the target technology field. Based on the expanded technology list, a focused search is performed within a specified range and in a specified direction to obtain target search results for the target technology field within the specified range and in the specified direction. The specified range is used to characterize the data range of the search, and the specified direction is used to characterize the focus direction selected from the multiple technology points. Based on the target retrieval results, time-series processing and information extraction and integration are performed to obtain trend analysis results in the target technology field.

2. The method according to claim 1, characterized in that, The pre-search processing based on the target technical field includes: The target technical field is searched using a search engine to obtain relevant information; Based on the associated information, an analysis and processing instruction for the target technical field is generated. The analysis and processing instruction includes technical points extracted from the associated information and processing methods for the technical points. Based on the analysis and processing instructions, the associated information is extracted and classified.

3. The method according to claim 2, characterized in that, The step of using a search engine to retrieve relevant information in the target technical field includes: Based on the search engine, keywords are expanded for the target technology field to obtain extended keywords; Perform a search operation based on the expanded keywords to obtain search results; The relevant information that meets the set requirements in terms of relevance to the target technical field is obtained from the search results.

4. The method according to claim 2, characterized in that, The step of generating analysis and processing instructions for the target technical field based on the associated information includes: Extract and set key information from the associated information; Based on the key information and preset command rules, the analysis and processing instructions are generated.

5. The method according to claim 1, characterized in that, The specified range refers to the data range of the defined search engine; the focused retrieval based on the expanded technology list within the specified range and in the specified direction includes: Receive a specified direction selected based on the list of extended technologies; Based on the established search engine, a first focused search is performed in the specified direction.

6. The method according to claim 1, characterized in that, The specified scope refers to a designated professional database; the focused retrieval based on the expanded technology list within the specified scope and in the specified direction includes: Receive a specified direction selected based on the list of extended technologies; A second focused search is performed on the specified direction based on the established professional database.

7. The method according to claim 1, characterized in that, Before performing time-series processing and information extraction and integration based on the target retrieval results, the method further includes: Filter the target search results for data that meets the set time range, whose correlation with multiple technical points meets the set correlation threshold range, and whose data source meets the set data source range; Based on the filtering results, update the target search results.

8. The method according to claim 1, characterized in that, The time-series processing and information extraction and integration based on the target retrieval results include: The target retrieval results are processed by time series analysis to obtain academic trend analysis results that characterize the technological development and change trends of the target technology field and the popularity of the multiple technology points.

9. The method according to claim 8, characterized in that, The time-series processing and information extraction and integration based on the target retrieval results also includes: Based on the target retrieval results and the academic trend analysis results, a technology development trend analysis instruction is generated; In response to the technology development trend analysis command, the system performs pre-set information extraction and integration corresponding to the type of technology development trend to obtain the technology development trend analysis results. The technology development trend analysis instruction carries the type of technology development trend.

10. A data trend analysis device, characterized in that, The device includes: The receiving module is used to receive the target technical field to be analyzed; An extension module is used to perform pre-search processing based on the target technology field and generate an expanded technology list, which includes multiple technology points that are consistent with the technology direction of the target technology field. The retrieval module is used to perform focused retrieval within a specified range and in a specified direction based on the expanded technology list, and to obtain target retrieval results for the target technology field within the specified range and in the specified direction. The specified range is used to characterize the data range of the retrieval, and the specified direction is used to characterize the focus direction selected from the multiple technology points. The information integration module is used to perform time-series processing and information extraction and integration based on the target retrieval results to obtain trend analysis results in the target technology field.

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