CN115439276A - Intellectual property management system and method based on big data and storage medium - Google Patents
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Abstract
The invention relates to the technical field of data management systems, in particular to an intellectual property right management system, method and storage medium based on big data, wherein the method comprises the following steps: s100, acquiring the category of a target to be evaluated, wherein the category of the target to be evaluated comprises enterprises and individuals; s200, judging whether the type of the target to be evaluated is an enterprise, if so, executing S300; s300, acquiring historical dispute data and patent declaration data of a target to be evaluated, wherein the patent declaration data comprises a ratio of field quantity involved in a declared patent to total quantity of the declared patent; and S400, analyzing the cooperation risk according to the historical dispute data and the patent declaration data, and generating a cooperation risk evaluation result. By adopting the scheme, the risk assessment accuracy can be improved, and the risk in the enterprise operation process is reduced.
Description
Technical Field
The invention relates to the technical field of data management systems, in particular to an intellectual property right management system, method and storage medium based on big data.
Background
In the current society, competition among enterprises is intensified, and any potential risk can bring huge loss to one enterprise. In the operation process of the enterprise, the enterprise does not need to cooperate with other enterprises, the cooperation starts from respective profit-making through cooperation, but if the risk of one cooperation enterprise is too large, the cooperation can not bring profits to the enterprise, and even can cause loss to the benefit of the enterprise. It follows that good operation of an enterprise does not leave accurate risk assessment.
Currently, before each enterprise is ready to perform business cooperation with other enterprises, the risk of the enterprise cooperation is evaluated in a back-tone mode and the like, and the risk mainly relates to past legal disputes, credit evaluation and the like of the corresponding enterprise, so that whether the enterprise has larger or more problems in the past cooperation process can be directly reflected. The problem of the enterprise exists not only in the direct interest dispute, but also in the dispute of the intangible asset of the intellectual property right, even because the intellectual property right is an intangible asset, the loss of the intangible asset is irreversible, so that the importance of whether the evaluation and the cooperation of the evaluation possibly damage the intellectual property right of the company is higher when the risk evaluation is carried out on the enterprise. The existing intellectual property risk assessment is usually only used for judging patent dispute quantity, the assessment is too unilateral, the accuracy is low, and a risk assessment result with high accuracy cannot be provided for enterprises.
Disclosure of Invention
The invention provides an intellectual property management system, method and storage medium based on big data, which can improve the accuracy of risk assessment and reduce the risk in the enterprise operation process.
The invention provides a first basic scheme:
the intellectual property management method based on the big data comprises the following steps:
s100, acquiring the category of a target to be evaluated, wherein the category of the target to be evaluated comprises enterprises and individuals;
s200, judging whether the type of the target to be evaluated is an enterprise, if so, executing S300;
s300, acquiring historical dispute data and patent declaration data of a target to be evaluated, wherein the patent declaration data comprises a ratio of field quantity involved in a declared patent to total quantity of the declared patent;
and S400, analyzing the cooperation risk according to the historical dispute data and the patent declaration data, and generating a cooperation risk evaluation result.
The beneficial effects of the first basic scheme are as follows:
risks in the enterprise operation process are mainly divided into external risks and internal risks, when the enterprise is cooperated with other enterprises, risks existing in the external enterprises and risks of internal data leakage of internal employees of the enterprises are mainly analyzed, and the risks correspond to the enterprises and individuals in the scheme respectively.
Specifically, the category of the target to be evaluated is obtained, and when the target to be evaluated is an enterprise, historical dispute data and patent declaration data of the target to be evaluated are obtained, and the cooperation risk is analyzed according to the historical dispute data and the patent declaration data. Compared with the prior art, the patent declaration data of the target to be evaluated is analyzed in the scheme, the ratio of the domain quantity involved in the declaration of the patent to the total quantity of the declared patent is included, and therefore the divergence degree of the research and development directions of the enterprise in the operation process can be obtained, for example, the enterprise is small in scale, but more patents are declared, the domains related to the patents are far away, the problem of the patent declaration behaviors is solved, and the improper behaviors are not eliminated; for example, an enterprise has a large scale and is dedicated to research and development in a small number of technical fields, but the patent application technical field is complicated, which indicates that patent application behaviors of the enterprise may have certain problems. Therefore, the scheme can be combined with the patent declaration data of the target to be evaluated, and the cooperation risk of the enterprise can be analyzed more comprehensively and accurately, so that the risk evaluation accuracy is improved, and the risk in the operation process of the enterprise is reduced.
Further, S400 includes:
s401, analyzing historical cooperation risk of the target to be evaluated according to the historical dispute data, and generating a historical cooperation risk evaluation result;
s402, analyzing the cooperation risk of the target to be evaluated according to the historical cooperation risk evaluation result and the patent application data, and generating a cooperation risk evaluation result.
Has the advantages that: the method comprises the steps of firstly, analyzing historical cooperation risks of a target to be evaluated according to visual historical dispute data, and then carrying out deep analysis on the risks of the target to be evaluated according to patent declaration data and historical cooperation risk evaluation results, so that the accuracy of the analysis results is improved. The historical dispute data of an enterprise is more, the patent declaration data shows that the ratio of the domain quantity involved in the declared patent to the total quantity of the declared patent is larger, and the probability that the enterprise generates disputes with other enterprises in the past cooperation process is higher, so that the potential risk of cooperation with the enterprise is higher.
Further, the historical dispute data comprises historical dispute quantity and historical dispute result.
Has the advantages that: and acquiring more comprehensive historical dispute data, thereby more accurately evaluating the risk of the enterprise. Specifically, the historical dispute amount may reflect whether the past cooperation process of the enterprise generates more disputes, and the historical dispute result may reflect whether the past cooperation process of the enterprise is a wrong party.
Further, S300 includes:
s301, acquiring pre-cooperation content of a target to be evaluated, wherein the pre-cooperation content comprises cooperation items and cooperation amount;
s302, analyzing whether the necessity of evaluating the target to be evaluated exceeds the preset enterprise necessary grade or not according to the pre-cooperation content, if so, acquiring historical dispute data and patent declaration data of the target to be evaluated, and if not, carrying out risk evaluation on the target to be evaluated.
Has the advantages that: firstly, whether the risk assessment of the target to be assessed is necessary or not is judged according to the cooperation items and the cooperation amount, so that the system analysis amount is reduced, and the analysis efficiency is improved.
Further, in S200, judging whether the type of the target to be evaluated is an enterprise, if not, executing S3;
s3, acquiring abnormal data of the target to be evaluated, wherein the abnormal data comprises an abnormal income data condition, an abnormal data condition of the coming and going personnel and an abnormal work content condition;
and S4, analyzing the leakage risk according to the abnormal data, and generating a leakage risk evaluation result.
Has the advantages that: and judging whether the category of the target to be evaluated is an enterprise, if not, indicating that the target to be evaluated is an individual, and performing risk evaluation in different modes. The abnormal data of the target to be evaluated is obtained, whether enterprise data leakage possibility exists is analyzed, the abnormal situation of income data, the abnormal situation of data of people coming and going and the abnormal situation of work content are included, whether important data leakage possibility exists in the target to be evaluated by utilizing the job is comprehensively analyzed, and therefore response measures can be made in advance.
Further, S3 includes:
s31, acquiring working data of a target to be evaluated, wherein the working data comprises post information, confidential document reference authority and job experience;
and S32, analyzing whether the necessity of evaluating the target to be evaluated exceeds a preset personal necessity level or not according to the working data, if so, acquiring abnormal data of the target to be evaluated, and if not, not evaluating the risk of the target to be evaluated.
Has the advantages that: firstly, whether the risk assessment of the target to be assessed is necessary or not is judged according to the post information, the confidential document reference authority and the empowerment experience of the target to be assessed, so that the system analysis amount is reduced, and the analysis efficiency is improved.
Further, S500 is included, and risk early warning is generated according to the cooperation risk assessment result or the leakage risk assessment result.
Has the advantages that: and generating a risk early warning according to the cooperation risk evaluation result or the leakage risk evaluation result, reminding the risk inside and outside the enterprise, and being convenient for preventing in time.
The invention provides a second basic scheme:
the intellectual property management system based on the big data uses the intellectual property management method based on the big data.
The second basic scheme has the beneficial effects that:
and acquiring the category of the target to be evaluated, and when the target to be evaluated is an enterprise, acquiring historical dispute data and patent declaration data of the target to be evaluated, and analyzing the cooperation risk according to the historical dispute data and the patent declaration data. Compared with the prior art, the method and the device have the advantages that the patent application data of the target to be evaluated are analyzed, the ratio of the field quantity involved in the application of the patent to the total quantity of the application of the patent is included, and therefore the divergence degree of the research and development directions of the enterprise in the operation process can be obtained, for example, the enterprise is small in scale, but more patents are applied, the fields related to the patents are far apart, the problem of the patent application behaviors is shown, and the improper behaviors are not eliminated; for example, an enterprise has a large scale and is dedicated to research and development in a small number of technical fields, but the patent application technical field is complicated, which indicates that patent application behaviors of the enterprise may have certain problems. Therefore, the scheme can be combined with the patent application data of the target to be evaluated, and the cooperation risk of an enterprise can be analyzed more accurately, so that the risk evaluation accuracy is improved, and the risk in the operation process of the enterprise is reduced.
The invention provides a third basic scheme:
the intellectual property management storage medium based on big data is used for storing computer executable instructions which realize the intellectual property management method based on big data when being executed.
The third basic scheme has the beneficial effects that:
and acquiring the category of the target to be evaluated, and when the target to be evaluated is an enterprise, acquiring historical dispute data and patent declaration data of the target to be evaluated, and analyzing the cooperation risk according to the historical dispute data and the patent declaration data. Compared with the prior art, the method and the device have the advantages that the patent application data of the target to be evaluated are analyzed, the ratio of the field quantity involved in the application of the patent to the total quantity of the application of the patent is included, and therefore the divergence degree of the research and development directions of the enterprise in the operation process can be obtained, for example, the enterprise is small in scale, but more patents are applied, the fields related to the patents are far apart, the problem of the patent application behaviors is shown, and the improper behaviors are not eliminated; for example, an enterprise has a large scale and specializes in research and development in a small number of technical fields, but the patent application technical field is complicated, which indicates that the patent application behavior of the enterprise may have certain problems. Therefore, the scheme can be combined with the patent declaration data of the target to be evaluated, and the cooperation risk of the enterprise can be analyzed more accurately, so that the risk evaluation accuracy is improved, and the risk in the operation process of the enterprise is reduced.
Drawings
Fig. 1 is a flow chart of an intellectual property management method based on big data according to an embodiment of the present invention.
Detailed Description
The following is further detailed by way of specific embodiments:
example 1:
the intellectual property management method based on big data, as shown in fig. 1, includes the following steps:
s100, acquiring the category of a target to be evaluated, wherein the category of the target to be evaluated comprises enterprises and individuals; the enterprise may perform risk assessment for the business enterprise and internal employees.
S200, judging whether the type of the target to be evaluated is an enterprise, if so, executing S300, and if not, executing S3; risk assessment is performed separately for businesses and individuals in different ways.
S300, acquiring historical dispute data and patent declaration data of a target to be assessed, wherein the historical dispute data comprises historical dispute quantity and historical dispute results, and the patent declaration data comprises a ratio of field quantity involved in a declared patent to total quantity of the declared patent; s300 comprises the following steps:
s301, acquiring pre-cooperation content of the target to be evaluated, wherein the pre-cooperation content comprises cooperation items and cooperation amount.
S302, analyzing whether the necessity of evaluating the target to be evaluated exceeds the preset enterprise necessary grade or not according to the pre-cooperation content, if so, acquiring historical dispute data and patent declaration data of the target to be evaluated, and if not, carrying out risk evaluation on the target to be evaluated. In this embodiment, it is determined whether the cooperation item is one of the pre-stored item types, and whether the cooperation amount is greater than a preset amount corresponding to the preset item type, if yes, it is determined that the necessity exceeds a preset enterprise necessity level, otherwise, there is no need for risk assessment.
And S400, analyzing the cooperation risk according to the historical dispute data and the patent declaration data, and generating a cooperation risk evaluation result. S400 includes:
s401, analyzing historical cooperative risk of the target to be evaluated according to historical dispute data, and generating a historical cooperative risk evaluation result; in the embodiment, the cooperative quantity and the dispute quantity of the target to be evaluated in the last two years are obtained, the ratio of the dispute quantity to the cooperative quantity is calculated, whether the ratio of the dispute quantity to the cooperative quantity is greater than thirty percent or not is analyzed, and if yes, the historical cooperative risk of the enterprise is judged to be first grade; if the historical collaboration risk is more than fifteen percent and less than or equal to thirty percent, judging the historical collaboration risk of the enterprise to be two-level; if the historical cooperation risk is larger than five percent and smaller than or equal to fifteen percent, judging that the historical cooperation risk of the enterprise is three levels; and if the historical collaboration risk is less than or equal to five percent, judging that the historical collaboration risk of the enterprise is four levels.
S402, analyzing the cooperation risk of the target to be evaluated according to the historical cooperation risk evaluation result and the patent declaration data, and generating a cooperation risk evaluation result. In this embodiment, the historical cooperation risk assessment result is adjusted according to the patent application data to serve as the cooperation risk assessment result. Specifically, the patent declaration data includes dispute patent fields, dispute object development fields corresponding to dispute patents, and a ratio of field quantities involved in the declared patents to total declared patents; judging whether the dispute patent field is a research and development field of an object to be evaluated, if so, judging whether the ratio of the domain quantity involved in the declared patent to the total quantity of the declared patent is larger than a preset domain ratio (if so, increasing the first-stage historical cooperation risk evaluation result to serve as a cooperation risk evaluation result, otherwise, directly using the historical cooperation risk evaluation result as a cooperation risk evaluation result), and if not, judging whether the dispute patent field is a dispute object research and development field corresponding to the dispute patent (if so, increasing the two-stage historical cooperation risk evaluation result to serve as a cooperation risk evaluation result, and if not, increasing the first-stage historical cooperation risk evaluation result to serve as a cooperation risk evaluation result). If the adjustment process cannot be increased continuously, if the historical cooperation risk evaluation result of an enterprise shows that the historical cooperation risk is in a second level and the adjustment is required for the two levels, the adjustment process can be performed only in the first level, and at the moment, a comment is generated to indicate that the adjustment is required for the first level so as to be convenient for a user to check.
S3, acquiring abnormal data of the target to be evaluated, wherein the abnormal data comprises an abnormal income data condition, an abnormal data condition of the coming and going personnel and an abnormal work content condition; s3 comprises the following steps:
and S31, acquiring working data of the target to be evaluated, wherein the working data comprises post information, confidential document reference permission and job experience.
And S32, analyzing whether the necessity of evaluating the target to be evaluated exceeds a preset personal necessity level or not according to the working data, if so, acquiring abnormal data of the target to be evaluated, and if not, not evaluating the risk of the target to be evaluated. In this embodiment, when the post information shows that the post is higher than the preset post, the confidential document inquiry authority shows that the authority range includes the confidential range, and the arbitrary experience shows that the average working life of one company is less than the preset life, it is determined whether the necessity of evaluating the object to be evaluated exceeds the preset personal necessity level.
And S4, analyzing the leakage risk according to the abnormal data, and generating a leakage risk evaluation result. In the embodiment, when the income data abnormal condition shows that abnormal income exists in nearly half a year, the data abnormal condition of the person who comes and goes shows that the person who comes and goes in nearly half a year and the staff of the enterprise in the research and development field exist, and the abnormal condition of the working content shows that the frequency of looking up the classified range file is higher than the frequency threshold, a leakage risk evaluation result with leakage risk is generated, otherwise, the leakage risk does not exist.
And S500, generating a risk early warning according to the cooperation risk assessment result or the leakage risk assessment result, and reminding the enterprise of the existence of the cooperation risk or the individual of the leakage risk. In this embodiment, when the category of the target to be assessed is an enterprise, if the cooperation risk assessment result shows that the cooperation risk is greater than or equal to two levels, a risk early warning is generated; and when the category of the target to be evaluated is personal, generating a risk early warning if the leakage risk evaluation result shows that the leakage risk exists.
The intellectual property management system based on the big data uses the intellectual property management method based on the big data.
The intellectual property management storage medium based on big data is used for storing computer executable instructions, and when the computer executable instructions are executed, the intellectual property management method based on big data is realized.
Example 2:
example 2 the basic principle is the same as example 1, except that example 2 further comprises the following steps:
s600, acquiring enterprise research and development content, extracting technical keywords, generating a search formula according to the technical keywords, and searching the published patents;
s700, analyzing the similarity between the published patent and the research and development content of the enterprise, judging whether the similarity is higher than a similarity threshold value, if so, executing S800;
s800, acquiring the disclosure of the inventor of the published patent, judging whether an unfamiliar inventor is included, and if so, executing S900;
and S900, acquiring the applicant of the published patent, analyzing whether the employees of the applicant comprise the employees of the enterprise, specifically, the employees of the enterprise are the employees who leave the enterprise for about two years, if so, analyzing whether the fields related to the work of the employees of the enterprise are the fields related to the research and development content of the enterprise, and if so, generating a scheme leakage prompt.
Therefore, after the employees leave the office, whether the technical ideas of the enterprise are leaked to other companies can be monitored in real time, so that the employees firstly apply for patents and the rights and interests of the enterprise are possibly damaged. And whether the published patent comprises the unfamiliar inventor or not is judged, whether the possibility of enterprise departure personnel participation exists in the patent is further judged, and therefore the accuracy of judging the scheme leakage is improved.
Example 3:
embodiment 3 is the same in basic principle as embodiment 1 except that S600 of embodiment 3 includes the steps of:
s601, acquiring enterprise research and development content, extracting technical keywords, and generating a primary search formula according to the technical keywords;
s602, acquiring field information of enterprise research and development content, acquiring related fields according to the field information, and forming a field set;
s603, obtaining a first common keyword when the patents of the field set are searched; in the embodiment, a first common keyword is obtained in a big data mode;
s604, analyzing the relevance between the keywords in the primary search formula and the first common keywords, and generating a first relevance analysis result;
s605, if the relevance is higher than the relevance threshold value as a result of the first relevance analysis, adding the first common keywords into the primary search formula, and generating a middle-level search formula; in this embodiment, the first common keyword is added to the keyword in the primary search formula with the highest relevance, and is connected by "OR", for example, if the keyword in the primary search formula is "intellectual property," the first common keyword is "known product," and "intellectual property OR known product" is generated as a new keyword in the intermediate search formula.
S606, acquiring a research and development theme of enterprise research and development content, and acquiring a second common keyword when a patent of the research and development theme is searched; under the same research and development theme, the technical fields of the patents may be different, so the keywords are added according to the research and development theme of the enterprise research and development content in the scheme;
s607, analyzing the relevance between the keywords in the primary search formula and the second common keywords, and generating a second relevance analysis result; the insertion mode of the second common keywords is the same as that of the first common keywords.
S608, if the relevance is higher than the relevance threshold value according to the second relevance analysis result, adding the second common key words into the intermediate-level search formula, and generating a high-level search formula;
and S609, searching the published patent according to the high-level searching formula.
By adopting the scheme, the comprehensiveness of the retrieval formula can be improved by selectively adding the patent retrieval keywords of the related fields or related research and development themes, so that the accuracy of the retrieval formula is improved. The traditional method usually depends on personal experience to expand the vocabulary in the retrieval formula, or expands the vocabulary in the retrieval formula by automatically generating similar keywords, but the former method needs to depend on the personal experience of the user, and meanwhile, people skilled in the technology and patents are few and have high difficulty; the latter, although able to expand the vocabulary, is too extensive and introduces too much noise, and the generated vocabulary may be irrelevant to the field, resulting in a lower accuracy of the search. By adopting the scheme, the user can be helped to automatically generate a more comprehensive search formula, and the accuracy is higher.
The foregoing are merely exemplary embodiments of the present invention, and no attempt is made to show structural details of the invention in more detail than is necessary for the fundamental understanding of the art, the description taken with the drawings making apparent to those skilled in the art how the several forms of the invention may be embodied in practice with the teachings of the invention. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (9)
1. The intellectual property management method based on big data is characterized by comprising the following steps: the method comprises the following steps:
s100, acquiring the category of a target to be evaluated, wherein the category of the target to be evaluated comprises enterprises and individuals;
s200, judging whether the type of the target to be evaluated is an enterprise, if so, executing S300;
s300, acquiring historical dispute data and patent declaration data of a target to be evaluated, wherein the patent declaration data comprises a ratio of field quantity involved in a declared patent to total quantity of the declared patent;
and S400, analyzing the cooperation risk according to the historical dispute data and the patent declaration data, and generating a cooperation risk evaluation result.
2. The intellectual property management method based on big data as claimed in claim 1, wherein: s400 includes:
s401, analyzing historical cooperative risk of the target to be evaluated according to historical dispute data, and generating a historical cooperative risk evaluation result;
s402, analyzing the cooperation risk of the target to be evaluated according to the historical cooperation risk evaluation result and the patent application data, and generating a cooperation risk evaluation result.
3. The intellectual property management method based on big data as claimed in claim 1, wherein: the historical dispute data comprises historical dispute quantity and historical dispute results.
4. The intellectual property management method based on big data as claimed in claim 1, wherein: s300 comprises the following steps:
s301, acquiring pre-cooperation content of a target to be evaluated, wherein the pre-cooperation content comprises cooperation items and cooperation amount;
s302, analyzing whether the necessity of evaluating the target to be evaluated exceeds a preset enterprise necessary grade or not according to the pre-cooperation content, if so, acquiring historical dispute data and patent declaration data of the target to be evaluated, and if not, not carrying out risk evaluation on the target to be evaluated.
5. The intellectual property management method based on big data as claimed in claim 1, wherein: in S200, judging whether the type of the target to be evaluated is an enterprise, if not, executing S3;
s3, acquiring abnormal data of the target to be evaluated, wherein the abnormal data comprises an abnormal income data condition, an abnormal data condition of the coming and going personnel and an abnormal work content condition;
and S4, analyzing the leakage risk according to the abnormal data, and generating a leakage risk evaluation result.
6. The intellectual property management method based on big data as claimed in claim 5, wherein: s3 comprises the following steps:
s31, acquiring working data of a target to be evaluated, wherein the working data comprises post information, confidential document reference permission and job experience;
and S32, analyzing whether the necessity of evaluating the target to be evaluated exceeds a preset personal necessity level or not according to the working data, if so, acquiring abnormal data of the target to be evaluated, and if not, not evaluating the risk of the target to be evaluated.
7. The intellectual property management method based on big data as claimed in claim 5, characterized in that: s500, generating a risk early warning according to the cooperation risk assessment result or the leakage risk assessment result.
8. Intellectual property right management system based on big data, its characterized in that: the intellectual property management method based on big data of any claim 1-7 is used.
9. An intellectual property management storage medium based on big data for storing computer executable instructions, characterized in that: the computer executable instructions, when executed, implement the big data based intellectual property management method of any one of the above claims 1-7.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211275020.0A CN115439276A (en) | 2022-10-18 | 2022-10-18 | Intellectual property management system and method based on big data and storage medium |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202211275020.0A CN115439276A (en) | 2022-10-18 | 2022-10-18 | Intellectual property management system and method based on big data and storage medium |
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| CN115439276A true CN115439276A (en) | 2022-12-06 |
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| CN202211275020.0A Pending CN115439276A (en) | 2022-10-18 | 2022-10-18 | Intellectual property management system and method based on big data and storage medium |
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