A patent analysis system based on big data

Abstract

The application discloses a kind of patent analysis systems based on big data, including data collection and integration unit, user demand analysis unit, custom service unit, personalized recommendation service unit, visual analysis unit and security privacy unit;User demand analysis unit is used to identify the specific needs of different users;Custom service unit is used for user access and understanding the information related to its field of interest;Personalized recommendation service unit provides relevant patents and information for users;Visual analysis unit is used to help users understand information;Security privacy unit is used for user data protection and legal use.The application makes personalized scheme for the needs of users, so that users can quickly access and understand the relevant information of their field of interest, and provide relevant patents and information for users according to their historical behavior and preferences, so that users can obtain patent information more quickly and accurately, and make patent analysis more flexible.

Description

Technical Field

[0001] This invention relates to the field of intellectual property analysis technology, and in particular to a patent analysis system based on big data. Background Technology

[0002] Patents are an important legal tool for protecting innovation, providing inventors with exclusive rights and promoting technological progress and business development. Therefore, whether it is an individual or a company, when filing a patent application or project proposal, it is necessary to conduct a patent search in order to understand the existing patent technologies in the patent field to which the project is to be filed.

[0003] Existing patent search and analysis methods are user-defined, requiring users to determine the search category and objectives themselves. This approach fails to provide analytical suggestions or customize the search based on the user's intended scope. Consequently, the content obtained during patent analysis is limited, lacking comprehensive analytical flexibility and the ability to offer recommendations, making patent analysis inflexible. Therefore, this solution proposes a big data-based patent analysis system to address these issues. Summary of the Invention

[0004] The purpose of this invention is to provide a patent analysis system based on big data to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a patent analysis system based on big data, the analysis system comprising a data collection and integration unit, a user demand analysis unit, a customized service unit, a personalized recommendation service unit, a visualization analysis unit, and a security and privacy unit;

[0006] The data collection and integration unit is used to collect and integrate patent data from different patent databases and external data sources, and to process the data.

[0007] The user needs analysis unit collects user information and analyzes user behavior data to identify the specific needs of different users;

[0008] The customized service unit provides customizable dashboards and customized analysis reports based on user needs analysis, enabling users to access and understand information related to their areas of interest;

[0009] The personalized recommendation service unit uses recommendation algorithms to provide users with relevant patents and information based on their historical behavior and preferences;

[0010] The visualization analysis unit displays data and trends graphically to help users understand information;

[0011] The security and privacy unit is used for the protection and lawful use of user data.

[0012] Preferably, the data collection and integration unit includes a patent database module, a text data processing module, and a data source module;

[0013] The patent database module is used for the collection and integration of patents by collecting patent content from the patent database.

[0014] The text data processing module uses natural language processing technology to preprocess the collected patent texts;

[0015] The data source module is used to combine industry reports, research papers, and market trends to increase the dimensions of analysis.

[0016] Preferably, the preprocessing includes word segmentation, stop word removal, and stemming.

[0017] Preferably, the user demand analysis unit includes a user registration module, an information collection module, and a behavior data analysis module;

[0018] The user registration module is used for user account registration;

[0019] The information collection module is used to collect basic user information;

[0020] The behavioral data analysis module is used to analyze user behavior data within the system.

[0021] Preferably, the behavioral data analysis module analyzes the user's search history, click behavior, and download history.

[0022] Preferably, the customization service unit includes a personalized dashboard module and a customized report generation module;

[0023] The personalized dashboard module is used to display patents, industry trends, and competitor analysis information that users are interested in;

[0024] The customized report generation module provides patent analysis reports based on user needs, including patent trends, technology maps, and competitive analysis.

[0025] Preferably, the recommendation algorithm analyzes user interests and behaviors to recommend relevant patents and information to users, and the algorithm is a content-based recommendation algorithm.

[0026] Preferably, the content-based recommendation algorithm includes user preference modeling and patent recommendation, wherein the user preference modeling is expressed as:

[0027] (1);

[0028] in, This represents the set of patents rated by user u. Represents the feature vector of patent i;

[0029] The patent recommendation is expressed as follows:

[0030] (2).

[0031] Preferably, the visualization analysis unit includes a data visualization module and an interactive query module;

[0032] The data visualization module uses graphical representations of data to help users discover potential trends and patterns.

[0033] The interactive query module is used for users to query data themselves.

[0034] Preferably, the security and privacy unit implements data security measures to prevent data leakage and misuse.

[0035] The technical effects and advantages of this invention are as follows:

[0036] This invention first analyzes user needs to understand the user's background, requirements, and preferences. Then, it proposes personalized solutions based on the user's needs, enabling the user to quickly access and understand relevant information in their areas of interest. Finally, it provides personalized recommendations based on the user's historical behavior and preferences, offering relevant patents and information. This allows users to obtain patent information more quickly and accurately, and makes patent search and analysis more flexible. Attached Figure Description

[0037] Figure 1 This is a schematic diagram of the system structure of the present invention. Detailed Implementation

[0038] 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, and 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.

[0039] This invention provides, for example Figure 1 The patent analysis system based on big data shown includes a data collection and integration unit, a user demand analysis unit, a customized service unit, a personalized recommendation service unit, a visualization analysis unit, and a security and privacy unit.

[0040] The data collection and integration unit is used to collect and integrate patent data from different patent databases and external data sources, and to process the data.

[0041] Specifically, the data collection and integration unit includes a patent database module, a text data processing module, and a data source module;

[0042] The patent database module is used for the collection and integration of patents by collecting patent content from the patent database;

[0043] It should be noted that the patent information collected includes the patent text, applicant information, inventor information, legal status, and citation details. The data is sourced from patent databases, including USPTO, EPO, and WIPO, to obtain the latest patent information.

[0044] The text data processing module uses natural language processing technology to preprocess the collected patent texts, providing structured and operable data for subsequent analysis and improving the efficiency of data analysis.

[0045] Furthermore, the preprocessing includes word segmentation, stop word removal, and stemming.

[0046] It should be noted that Natural Language Processing (NLP) is a field of artificial intelligence and computer science that enables computers to understand, interpret, and generate natural language. NLP technology combines linguistics, computer science, and statistics and is applied in various practical scenarios.

[0047] The main purpose of this section is to establish a comprehensive and accurate foundation for patent information. By integrating data from different patent databases and external data sources, the system can provide comprehensive patent analysis, helping users obtain the latest patent dynamics, technological trends, and competitive intelligence. Data collection and integration ensure the depth and breadth of the system's analysis, forming the basis for subsequent analysis and services.

[0048] The data source module is used to combine industry reports, research papers, and market trends to increase the dimensions of analysis.

[0049] The user needs analysis unit collects user information and analyzes user behavior data to identify the specific needs of different users;

[0050] It should be noted that user needs analysis involves gaining a deep understanding of users' backgrounds, needs, and preferences. This process, through collecting user information and analyzing user behavior data, enables the system to identify the specific needs of different users, thus laying the foundation for personalized services and recommendations. Through these analyses, the system can better meet user expectations and improve user experience and satisfaction.

[0051] Specifically, the user needs analysis unit includes a user registration module, an information collection module, and a behavioral data analysis module;

[0052] The user registration module is used for user account registration. By understanding the user's background and needs, it lays the foundation for personalized services and ensures that the system can better meet the user's expectations.

[0053] The information collection module is used to collect basic user information, including user's areas of interest and corporate goals, through questionnaires and interviews.

[0054] The behavioral data analysis module is used to analyze user behavior data within the system.

[0055] Furthermore, the behavioral data analysis module analyzes users' search history, click behavior, and download history to identify user preferences, helping the system to make more accurate personalized recommendations and improve user experience.

[0056] The customized service unit provides customizable dashboards and customized analysis reports based on user needs analysis, enabling users to access and understand information relevant to their areas of interest;

[0057] It should be noted that the purpose of customized services is to provide personalized solutions based on the user's specific needs. This includes providing users with customizable dashboards and customized analysis reports, enabling users to quickly access and understand information relevant to their areas of interest. This part enhances the user's decision support capabilities by ensuring the relevance and usability of the information.

[0058] Specifically, the customized service unit includes a personalized dashboard module and a customized report generation module;

[0059] The personalized dashboard module is used to display patents, industry trends, and competitor analysis information that users are interested in. By providing users with a customizable dashboard, it enables users to quickly access the most relevant information and improves the efficiency of information acquisition.

[0060] The customized report generation module provides patent analysis reports based on user needs, including patent trends, technology maps, and competitive analysis. It generates reports according to specific user requirements, providing in-depth analysis and insights to help users make more informed decisions.

[0061] The personalized recommendation service unit uses recommendation algorithms to provide users with relevant patents and information based on their historical behavior and preferences;

[0062] It should be noted that personalized recommendation services utilize recommendation algorithms to provide users with relevant patents and information based on their historical behavior and preferences. This feature enhances the system's intelligence, helps users discover potential valuable information, and improves user experience and satisfaction. Personalized recommendations can improve the relevance of information and reduce users' information retrieval costs.

[0063] Specifically, the recommendation algorithm analyzes user interests and behaviors to recommend relevant patents and information to users, improving the system's intelligence and increasing user stickiness. At the same time, the system has the ability to update in real time, promptly pushing new patent-related information that users may be interested in, ensuring that users can obtain the latest information in a timely manner, helping them stay sensitive to industry dynamics and enhance their competitive advantage.

[0064] The algorithm is a content-based recommendation algorithm.

[0065] Furthermore, content-based recommendation algorithms include user preference modeling and patent recommendation. User preference modeling is represented as:

[0066] (1);

[0067] in, This represents the set of patents rated by user u. Represents the feature vector of patent i;

[0068] Patent recommendations are expressed as follows:

[0069] (2).

[0070] The visualization analytics unit presents data and trends graphically to help users understand information;

[0071] It should be noted that the purpose of visualization analysis is to present complex data and trends in a graphical way, helping users to understand information more intuitively. This part makes data analysis results easier to interpret. Users explore data interactively, discover potential relationships and patterns, and visualization tools improve the readability and operability of data, enabling users to make more informed decisions.

[0072] Specifically, the visualization analysis unit includes a data visualization module and an interactive query module;

[0073] The data visualization module uses graphical representations of data to help users understand complex information more intuitively and to facilitate the discovery of potential trends and patterns.

[0074] The interactive query module allows users to query data themselves, enabling them to freely explore the data, enhancing their sense of participation and initiative, and improving the efficiency of information acquisition.

[0075] The security and privacy unit is used to protect and legally use user data. It implements data security measures to prevent data leakage and misuse.

[0076] It should be noted that the security and privacy section ensures the protection and legal use of user data, enhances user trust in the system, and prevents data leakage and abuse by implementing data security measures and complying with relevant laws and regulations, thus protecting user privacy. At the same time, this section also reduces the system's legal risks and improves the system's reliability and reputation.

[0077] Among these, data security ensures the protection of user data, enhances user trust in the system, reduces the risk of data leakage, compliance follows laws and regulations, protects user privacy, avoids legal risks, and improves the reliability and reputation of the system.

[0078] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A patent analysis system based on big data, characterized in that, The analysis system includes a data collection and integration unit, a user demand analysis unit, a customized service unit, a personalized recommendation service unit, a visualization analysis unit, and a security and privacy unit. The data collection and integration unit is used to collect and integrate patent data from different patent databases and external data sources, and to process the data. The user needs analysis unit collects user information and analyzes user behavior data to identify the specific needs of different users; The customized service unit provides customizable dashboards and customized analysis reports based on user needs analysis, enabling users to access and understand information related to their areas of interest; The personalized recommendation service unit uses recommendation algorithms to provide users with relevant patents and information based on their historical behavior and preferences; The visualization analysis unit displays data and trends graphically to help users understand information; The security and privacy unit is used for the protection and lawful use of user data.

2. The patent analysis system based on big data according to claim 1, characterized in that, The data collection and integration unit includes a patent database module, a text data processing module, and a data source module; The patent database module is used for the collection and integration of patents by collecting patent content from the patent database. The text data processing module uses natural language processing technology to preprocess the collected patent texts; The data source module is used to combine industry reports, research papers, and market trends to increase the dimensions of analysis.

3. The patent analysis system based on big data according to claim 2, characterized in that, The preprocessing includes word segmentation, stop word removal, and stemming.

4. The patent analysis system based on big data according to claim 1, characterized in that, The user demand analysis unit includes a user registration module, an information collection module, and a behavior data analysis module. The user registration module is used for user account registration; The information collection module is used to collect basic user information; The behavioral data analysis module is used to analyze user behavior data within the system.

5. A patent analysis system based on big data according to claim 4, characterized in that, The behavioral data analysis module analyzes user search history, click behavior, and download history.

6. The patent analysis system based on big data according to claim 1, characterized in that, The customization service unit includes a personalized dashboard module and a customized report generation module; The personalized dashboard module is used to display patents, industry trends, and competitor analysis information that users are interested in; The customized report generation module provides patent analysis reports based on user needs, including patent trends, technology maps, and competitive analysis.

7. A patent analysis system based on big data according to claim 1, characterized in that, The recommendation algorithm analyzes user interests and behaviors to recommend relevant patents and information to users. The algorithm is a content-based recommendation algorithm.

8. A patent analysis system based on big data according to claim 7, characterized in that, The content-based recommendation algorithm includes user preference modeling and patent recommendation, wherein the user preference modeling is expressed as: （1）； in, This represents the set of patents rated by user u. Represents the feature vector of patent i; The patent recommendation is expressed as follows: （2）。 9. A patent analysis system based on big data according to claim 1, characterized in that, The visualization analysis unit includes a data visualization module and an interactive query module; The data visualization module uses graphical representations of data to help users discover potential trends and patterns. The interactive query module is used for users to query data themselves.

10. A patent analysis system based on big data according to claim 1, characterized in that, The security and privacy unit implements data security measures to prevent data leakage and misuse.

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