1. A big data-based enterprise intellectual property management method, wherein the method comprises:

obtaining a first predetermined area;

obtaining first enterprise library information according to the first preset area, wherein the first enterprise library comprises a plurality of enterprises;

sequentially obtaining first enterprise attribute information corresponding to each enterprise in the first enterprise library;

obtaining predetermined attribute information;

acquiring a set of enterprises meeting the preset attribute information in the first enterprise library according to the preset attribute information and the first enterprise attribute information;

establishing second enterprise repository information according to the set of enterprises meeting the preset attribute information in the first enterprise repository;

obtaining a first big data platform establishment instruction;

after the first big data platform establishing instruction is sent to each enterprise in the second enterprise library, obtaining confirmation information of each enterprise in the second enterprise library;

acquiring a set of confirmation information in the second enterprise library according to the confirmation information, and establishing third enterprise library information;

obtaining first intellectual property information of each enterprise in the third enterprise repository;

and establishing the first big data cloud platform according to the first big data platform establishing instruction and the first intellectual property information of each enterprise in the third enterprise library, wherein the first big data cloud platform is an intellectual property alliance platform.

2. The method of claim 1, wherein the obtaining first intellectual property information for each business in the third business repository comprises:

obtaining first design drawing information of each enterprise in the third enterprise library, wherein the first design drawing information is a public product design drawing;

obtaining first selling product information of each enterprise in the third enterprise library, wherein the first selling product information is an open product;

judging whether first production information exists in the third enterprise library, wherein the first production information comprises a first material and/or a first production method;

obtaining the first material, if present, and/or the first production method;

and obtaining the first intellectual property information according to the first design drawing information, the first production information, the first material and/or the first production method.

3. The method of claim 1, wherein after establishing the first big data cloud platform according to the first big data platform establishment instruction, the first intellectual property information of each enterprise in the third enterprise repository, the method comprises:

obtaining first manager information of each enterprise in the third enterprise library;

acquiring first service level information of the first manager information;

obtaining a predetermined traffic level capability;

judging whether the first service level information meets the preset service level capability or not;

and if the preset service level capability does not meet the requirement, acquiring first reminding information, and sending the first reminding information to the first manager who does not meet the preset service level capability.

4. The method of claim 3, wherein the obtaining first business level information for the first manager information comprises:

obtaining a first test instruction;

according to the first test instruction, obtaining a first test value after performing a service level test on each first manager;

obtaining first working information and first social attribute information of a first manager of each enterprise in the third enterprise library;

and obtaining first service level information of the first manager information according to the first test value, the first working information and the first social attribute information.

5. The method of claim 4, wherein the obtaining of the first business level information of the first manager information is based on the first test value, the first practitioner information, and the first social attribute information, the method comprising:

inputting the first test value, the first working information and the first social attribute information into a first neural network model, wherein the model is trained by using a plurality of groups of training data, and each group of training data in the plurality of groups comprises: the first test value, the first practitioner information, the first social attribute information and identification information identifying first business level information of a first administrator;

obtaining output information of the model, wherein the output information includes a first result, and the first result is first business level information of a first manager of each enterprise in the third enterprise repository.

6. The method of claim 3, wherein after establishing the first big data cloud platform according to the first big data platform establishment instruction, the first intellectual property information of each enterprise in the third enterprise repository, the method further comprises:

obtaining a first predetermined time interval;

acquiring second intellectual property data through the first big data cloud platform according to the first preset time interval;

and sending the second intellectual property data to the first manager.

7. The method of claim 6, wherein the method further comprises:

obtaining first planning drawing information sent by the first manager according to the first big data cloud platform;

judging whether the first planning drawing information meets a preset production condition or not based on the first big data cloud platform;

and if not, acquiring second reminding information and sending the second reminding information to the first manager.

8. An enterprise intellectual property management system based on big data, wherein the system comprises:

a first obtaining unit: the first obtaining unit is used for obtaining a first preset area;

a second obtaining unit: the second obtaining unit is used for obtaining first enterprise library information according to the first preset area, wherein the first enterprise library comprises a plurality of enterprises;

a third obtaining unit: the third obtaining unit is configured to sequentially obtain first enterprise attribute information corresponding to each enterprise in the first enterprise repository;

a fourth obtaining unit: the fourth obtaining unit is used for obtaining the predetermined attribute information;

a fifth obtaining unit: the fifth obtaining unit is configured to obtain, according to the predetermined attribute information and the first enterprise attribute information, a set of enterprises in the first enterprise repository that meet the predetermined attribute information;

a first establishing unit: the first establishing unit is used for establishing second enterprise library information according to the set of enterprises meeting the preset attribute information in the first enterprise library;

a sixth obtaining unit: the sixth obtaining unit is used for obtaining a first big data platform establishing instruction;

a seventh obtaining unit: the seventh obtaining unit is configured to obtain confirmation information from each enterprise in the second enterprise repository after the first big data platform establishment instruction is sent to each enterprise in the second enterprise repository;

a second establishing unit: the second establishing unit is used for acquiring a set of confirmation information in the second enterprise repository according to the confirmation information and establishing third enterprise repository information;

an eighth obtaining unit: the eighth obtaining unit is configured to obtain first intellectual property information of each enterprise in the third enterprise repository;

a third establishing unit: the third establishing unit is configured to establish the first big data cloud platform according to the first big data platform establishing instruction and the first intellectual property information of each enterprise in the third enterprise repository, where the first big data cloud platform is an intellectual property alliance platform.

9. A big data based enterprise intellectual property management system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method of any one of claims 1-7 when executing the program.

Background

With the continuous development of the society in China, the operators of enterprises pay more and more attention to the management of intellectual property rights of the enterprises, the management of intellectual property rights of the enterprises is a system engineering, the effective operation of the management system depends on a scientific management system, and the enterprises need to establish an effective intellectual property rights management system to facilitate the scientific management of the enterprise operation.

However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the inventors of the present application find that the above-mentioned technology has at least the following technical problems:

because some small and medium-sized enterprises have not deep understanding in the aspect of intellectual property rights, a reasonable intellectual property right management system is not provided, and the problems of delayed development of the enterprises and the like are caused.

Disclosure of Invention

The embodiment of the application provides the enterprise intellectual property management method and system based on the big data, solves the technical problem that the development of enterprises is lagged due to lack of intellectual property protection consciousness of the enterprises, achieves the technical effects that an intellectual property alliance platform is built based on the development of the enterprises, management and maintenance of intellectual property information and authorization cooperation among the enterprises are provided for small and medium-sized enterprises, the risk of infringement is effectively avoided, and high-quality development of the enterprises is assisted.

The embodiment of the application provides an enterprise intellectual property management method based on big data, wherein the method comprises the following steps: obtaining a first predetermined area; obtaining first enterprise library information according to the first preset area, wherein the first enterprise library comprises a plurality of enterprises; sequentially obtaining first enterprise attribute information corresponding to each enterprise in the first enterprise library; obtaining predetermined attribute information; acquiring a set of enterprises meeting the preset attribute information in the first enterprise library according to the preset attribute information and the first enterprise attribute information; establishing second enterprise repository information according to the set of enterprises meeting the preset attribute information in the first enterprise repository; obtaining a first big data platform establishment instruction; after the first big data platform establishing instruction is sent to each enterprise in the second enterprise library, obtaining confirmation information of each enterprise in the second enterprise library; acquiring a set of confirmation information in the second enterprise library according to the confirmation information, and establishing third enterprise library information; obtaining first intellectual property information of each enterprise in the third enterprise repository; and establishing the first big data cloud platform according to the first big data platform establishing instruction and the first intellectual property information of each enterprise in the third enterprise library, wherein the first big data cloud platform is an intellectual property alliance platform.

In another aspect, the present application further provides a system for enterprise intellectual property management based on big data, where the system includes: a first obtaining unit: the first obtaining unit is used for obtaining a first preset area; a second obtaining unit: the second obtaining unit is used for obtaining first enterprise library information according to the first preset area, wherein the first enterprise library comprises a plurality of enterprises; a third obtaining unit: the third obtaining unit is configured to sequentially obtain first enterprise attribute information corresponding to each enterprise in the first enterprise repository; a fourth obtaining unit: the fourth obtaining unit is used for obtaining the predetermined attribute information; a fifth obtaining unit: the fifth obtaining unit is configured to obtain, according to the predetermined attribute information and the first enterprise attribute information, a set of enterprises in the first enterprise repository that meet the predetermined attribute information; a first establishing unit: the first establishing unit is used for establishing second enterprise library information according to the set of enterprises meeting the preset attribute information in the first enterprise library; a sixth obtaining unit: the sixth obtaining unit is used for obtaining a first big data platform establishing instruction; a seventh obtaining unit: the seventh obtaining unit is configured to obtain confirmation information from each enterprise in the second enterprise repository after the first big data platform establishment instruction is sent to each enterprise in the second enterprise repository; a second establishing unit: the second establishing unit is used for acquiring a set of confirmation information in the second enterprise repository according to the confirmation information and establishing third enterprise repository information; an eighth obtaining unit: the eighth obtaining unit is configured to obtain first intellectual property information of each enterprise in the third enterprise repository; a third establishing unit: the third establishing unit is configured to establish the first big data cloud platform according to the first big data platform establishing instruction and the first intellectual property information of each enterprise in the third enterprise repository, where the first big data cloud platform is an intellectual property alliance platform.

One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

the enterprises which aggregate the preset attribute information and wish to join the intellectual property alliance platform and establish the enterprise database to establish the intellectual property alliance platform achieve the technical effects that managers can know the latest dynamic state of the industry in time, and meanwhile, management and maintenance of intellectual property information, authorization cooperation among the enterprises and the like can be provided for small and medium-sized enterprises.

The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.

Drawings

Fig. 1 is a schematic flowchart of a method for enterprise intellectual property management based on big data according to an embodiment of the present application;

fig. 2 is a schematic structural diagram of an enterprise intellectual property management system based on big data according to an embodiment of the present application;

fig. 3 is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application.

Description of reference numerals: a first obtaining unit 11, a second obtaining unit 12, a third obtaining unit 13, a fourth obtaining unit 14, a fifth obtaining unit 15, a first establishing unit 16, a sixth obtaining unit 17, a seventh obtaining unit 18, a second establishing unit 19, an eighth obtaining unit 20, a third establishing unit 21, a bus 300, a receiver 301, a processor 302, a transmitter 303, a memory 304, and a bus interface 305.

Detailed Description

The embodiment of the application provides the enterprise intellectual property management method and system based on the big data, solves the technical problem that the development of enterprises is lagged due to lack of intellectual property protection consciousness of the enterprises, achieves the technical effects that an intellectual property alliance platform is built based on the development of the enterprises, management and maintenance of intellectual property information and authorization cooperation among the enterprises are provided for small and medium-sized enterprises, the risk of infringement is effectively avoided, and high-quality development of the enterprises is assisted.

Hereinafter, example embodiments according to the present application will be described in detail with reference to the accompanying drawings. It should be apparent that the described embodiments are merely some embodiments of the present application and not all embodiments of the present application, and it should be understood that the present application is not limited to the example embodiments described herein.

Summary of the application

With the continuous development of the society in China, the operators of enterprises pay more and more attention to the management of intellectual property rights of the enterprises, the management of intellectual property rights of the enterprises is a system engineering, the effective operation of the management system depends on a scientific management system, and the enterprises need to establish an effective intellectual property rights management system to facilitate the scientific management of the enterprise operation. Because some small and medium-sized enterprises have not deep understanding in the aspect of intellectual property rights, a reasonable intellectual property right management system is not provided, and the problems of delayed development of the enterprises and the like are caused.

In view of the above technical problems, the technical solution provided by the present application has the following general idea:

the embodiment of the application provides an enterprise intellectual property management method based on big data, wherein the method comprises the following steps: obtaining a first predetermined area; obtaining first enterprise library information according to the first preset area, wherein the first enterprise library comprises a plurality of enterprises; sequentially obtaining first enterprise attribute information corresponding to each enterprise in the first enterprise library; obtaining predetermined attribute information; acquiring a set of enterprises meeting the preset attribute information in the first enterprise library according to the preset attribute information and the first enterprise attribute information; establishing second enterprise repository information according to the set of enterprises meeting the preset attribute information in the first enterprise repository; obtaining a first big data platform establishment instruction; after the first big data platform establishing instruction is sent to each enterprise in the second enterprise library, obtaining confirmation information of each enterprise in the second enterprise library; acquiring a set of confirmation information in the second enterprise library according to the confirmation information, and establishing third enterprise library information; obtaining first intellectual property information of each enterprise in the third enterprise repository; and establishing the first big data cloud platform according to the first big data platform establishing instruction and the first intellectual property information of each enterprise in the third enterprise library, wherein the first big data cloud platform is an intellectual property alliance platform.

For better understanding of the above technical solutions, the following detailed descriptions will be provided in conjunction with the drawings and the detailed description of the embodiments.

Example one

As shown in fig. 1, an embodiment of the present application provides a method for enterprise intellectual property management based on big data, where the method further includes:

step S100: obtaining a first predetermined area;

step S200: obtaining first enterprise library information according to the first preset area, wherein the first enterprise library comprises a plurality of enterprises;

specifically, the first predetermined area is a predetermined area, and the area includes various enterprises, and may be divided into large, medium, small, and micro enterprises according to the enterprise scale, and may be divided into factories, companies, initiatives, and the like according to the enterprise organization. And then, obtaining information of a first enterprise library according to the first predetermined area, wherein the first enterprise library comprises a plurality of enterprises, namely a plurality of enterprises form an industry of the first predetermined area, for example, Chinese multi-business clothing enterprises in cities such as Guangdong, Jiangsu, Zhejiang and the like form an industry chain of different clothing. The range of operation is very wide, and the clothes are popular with customers, such as children clothes, old people clothes and the like.

Step S300: sequentially obtaining first enterprise attribute information corresponding to each enterprise in the first enterprise library;

step S400: obtaining predetermined attribute information;

specifically, given the first enterprise repository information, first enterprise attribute information corresponding to each enterprise in the first enterprise repository may be sequentially obtained, where the first enterprise attribute information includes information such as enterprise scale, market location, customer popularity, product sales, product design style, and the like. The method can also obtain preset attribute information, the preset attribute information is preset enterprise attribute information, attribute screening can be carried out on each enterprise in the first enterprise library through preset specific enterprise attribute information, and then intellectual property management can be carried out on the screened enterprises, and the preset attribute information can be understood as attribute information of small and medium-sized enterprises, high customer popularity, novel product design and the like.

Step S500: acquiring a set of enterprises meeting the preset attribute information in the first enterprise library according to the preset attribute information and the first enterprise attribute information;

step S600: establishing second enterprise repository information according to the set of enterprises meeting the preset attribute information in the first enterprise repository;

specifically, given the first enterprise attribute information and the predetermined attribute information corresponding to each enterprise in the first enterprise repository, a set of enterprises satisfying the predetermined attribute information in the first enterprise repository can be obtained, that is, the enterprises satisfying the predetermined attribute information are screened out to be collected, and thus second enterprise repository information is established, where the second enterprise repository is formed by a set of enterprises of small and medium enterprise size, high customer popularity, novel product design, and the like, and the second enterprise repository is established to help further perform intellectual property management on the industry in the first predetermined area.

Step S700: obtaining a first big data platform establishment instruction;

specifically, big data (big data), an IT industry term, refers to a data set that cannot be captured, managed, and processed by a conventional software tool within a certain time range, and is a massive, high-growth-rate, diversified information asset that needs a new processing mode to have stronger decision-making power, insight discovery power, and process optimization capability. The platform is established based on big data, so that various resources are integrated, and great convenience is provided for enterprises and customers.

Step S800: after the first big data platform establishing instruction is sent to each enterprise in the second enterprise library, obtaining confirmation information of each enterprise in the second enterprise library;

step S900: acquiring a set of confirmation information in the second enterprise library according to the confirmation information, and establishing third enterprise library information;

specifically, it is known that the first big data platform establishment instruction may be sent to each enterprise in the second enterprise repository, and then confirmation information from each enterprise in the second enterprise repository is obtained, that is, each enterprise in the second enterprise repository selects whether to join the first big data platform, after the enterprise confirms to join the first big data platform, a set of confirmation information in the second enterprise repository may be obtained according to the confirmation information, and third enterprise repository information is established, and the third enterprise repository information is further refined to the second enterprise repository information, that is, the third enterprise repository is formed by an enterprise set confirmed to join the first big data platform, and the third enterprise repository information is established, so that intellectual property management may be further performed on the enterprise.

Step S1000: obtaining first intellectual property information of each enterprise in the third enterprise repository;

step S1100: and establishing the first big data cloud platform according to the first big data platform establishing instruction and the first intellectual property information of each enterprise in the third enterprise library, wherein the first big data cloud platform is an intellectual property alliance platform.

Specifically, it is known to establish the third enterprise repository information, and first intellectual property information of each enterprise in the third enterprise repository can be obtained. Intellectual property rights, also known as "intellectual property rights", refer to "exclusive rights which the rightist has in accordance with the laws on the production of intellectual work and the marking and reputation of the business activity", which are generally valid only for a limited period of time. When the method is applied to the industry, the design drawing information is embodied, and the design drawing information of a designer enjoys certain intellectual property protection. And then establishing the first big data cloud platform according to the first big data platform establishing instruction and the first intellectual property information of each enterprise in the third enterprise library, wherein the first big data cloud platform is an intellectual property alliance platform, namely, an intellectual property alliance is established based on the first intellectual property information of each enterprise in the third enterprise library, and the intellectual property platforms are established to provide management, maintenance and the like of the intellectual property information for the small and medium-sized enterprises, and meanwhile, the enterprises on the alliance platform can also be authorized and cooperated with one another.

Further, the obtaining the first intellectual property information of each enterprise in the third enterprise repository, step S1000 further includes:

step S1010: obtaining first design drawing information of each enterprise in the third enterprise library, wherein the first design drawing information is a public product design drawing;

step S1020: obtaining first selling product information of each enterprise in the third enterprise library, wherein the first selling product information is an open product;

step S1030: judging whether first production information exists in the third enterprise library, wherein the first production information comprises a first material and/or a first production method;

step S1040: obtaining the first material, if present, and/or the first production method;

step S1050: and obtaining the first intellectual property information according to the first design drawing information, the first production information, the first material and/or the first production method.

Specifically, in order to specifically obtain first intellectual property information of each enterprise in the third enterprise repository, first design drawing information of each enterprise in the third enterprise repository may be obtained, where the first design drawing information is a public product design drawing, and the public design drawing may be in a sense that the first design drawing information is an existing design drawing and may obtain a certain legal protection, and further obtain first sold product information of each enterprise in the third enterprise repository, where the first sold product information is a public product, that is, a product that has been produced and sold in a batch production line, for example, when the product is a clothing enterprise, and then it may be determined whether first production information exists in the third enterprise repository, where the first production information includes a first material, and/or, the first production method can be understood as whether new materials autonomously developed by enterprises exist in the third enterprise library, or new industry-related production methods, if any, the first material may be obtained, and/or, the first production method, and further obtaining the first intellectual property information based on the first design drawing information, the first production information, the first material, and/or the first production method, namely, the related information disclosed by each enterprise, including design drawing information, selling product information, researching and developing new materials or researching and developing new production methods, and the like, is stored and managed, and uploading to the first big data cloud platform, the technical effects of facilitating comparison and reference of newly designed information, and realizing benefit maximization by performing authorized cooperation among enterprises are achieved.

Further, after the first big data cloud platform is established according to the first big data platform establishment instruction and the first intellectual property information of each enterprise in the third enterprise repository, the embodiment of the present application further includes:

step 1210: obtaining first manager information of each enterprise in the third enterprise library;

step S1220: acquiring first service level information of the first manager information;

step S1230: obtaining a predetermined traffic level capability;

step S1240: judging whether the first service level information meets the preset service level capability or not;

step S1250: and if the preset service level capability does not meet the requirement, acquiring first reminding information, and sending the first reminding information to the first manager who does not meet the preset service level capability.

Specifically, in order to perform more effective intellectual property management on an enterprise, first manager information of each enterprise in the third enterprise repository may be obtained, where the first manager information includes comprehensive information of management ability, business literacy, business intercourse, and the like of a manager, and first service level information of the first manager information, that is, an ability to process a service, is obtained, and further a predetermined service level ability is obtained, where the predetermined service level ability is a preset excellent service level of the first manager, and can process each service quickly and with high quality, by determining whether the first service level information satisfies the predetermined service level ability, and if not, obtaining first reminding information, where the first reminding information is that the service level information of the first manager does not reach the predetermined service level ability, and meanwhile, the first reminding information is sent to the first manager who does not meet the preset service level capability, so that the first manager can carry out corresponding service training such as innovation and teaching, the service level capability of the manager is improved, and the technical effect of creating more benefits is achieved.

Further, the step S1220 of obtaining the first service level information of the first administrator information further includes:

step S1221: obtaining a first test instruction;

step S1222: according to the first test instruction, obtaining a first test value after performing a service level test on each first manager;

step S1223: obtaining first working information and first social attribute information of a first manager of each enterprise in the third enterprise library;

step S1224: and obtaining first service level information of the first manager information according to the first test value, the first working information and the first social attribute information.

Specifically, in order to further obtain first business level information of the first administrator information, a first test instruction may be obtained, where the first test instruction is to perform a business level test on each first administrator to obtain a first test value, the first test value is a business level test result, first professional information and first social attribute information of the first administrator of each enterprise in the third enterprise repository may also be obtained, the first professional information includes personal records and historical employment directions of the first administrator, the first social attribute information includes talents of the first administrator, such as talents of high academic record or other talents of independent creation, and the first business level information of the first administrator information may further be obtained according to the first test value, the first professional information, and the first social attribute information, for example, when the first administrator is a professional with high academic history and has rich experience and a good level test result, the service level of the first administrator is high, and the like, the service level of the administrator is evaluated in a professional manner by integrating multiple aspects, so that the technical effect of accurately obtaining the service level of the administrator is achieved.

Further, the step S1224 of obtaining the first business level information of the first administrator information according to the first test value, the first professional information, and the first social attribute information further includes:

step S12241: inputting the first test value, the first working information and the first social attribute information into a first neural network model, wherein the model is trained by using a plurality of groups of training data, and each group of training data in the plurality of groups comprises: the first test value, the first practitioner information, the first social attribute information and identification information identifying first business level information of a first administrator;

step S12242: obtaining output information of the model, wherein the output information includes a first result, and the first result is first business level information of a first manager of each enterprise in the third enterprise repository.

Specifically, in order to obtain more accurate first service level information of the first administrator, the first test value, the first practitioner information, and the first social attribute information may be input into the first neural network model for continuous training, so that the output training result may be more accurate. The first training model is a Neural network model, namely a Neural network model in machine learning, and a Neural Network (NN) is a complex Neural network system formed by widely interconnecting a large number of simple processing units (called neurons), reflects many basic features of human brain functions, and is a highly complex nonlinear dynamical learning system. Neural network models are described based on mathematical models of neurons. Artificial Neural Networks (Artificial Neural Networks) are a description of the first-order properties of the human brain system. Briefly, it is a mathematical model. In the embodiment of the application, the first test value, the first working information and the first social attribute information are input into a first neural network model for continuous training, and the first service level information of the identified first manager is used for training the neural network model.

Further, the process of training the neural network model is substantially a process of supervised learning. The plurality of groups of training data are specifically: the first test value, the first engagement information, the first social attribute information, and the identification information identifying the first business level information of the first administrator. The neural network model outputs a first training result through inputting the first test value, the first professional information and the first social attribute information, the first training result is first business level information of a first manager of each enterprise in the third enterprise library, the output information is verified with the first business level information of the first manager playing a role in identification, if the output information is consistent with the first business level information requirement of the first manager playing a role in identification, the data supervised learning is finished, and then the next group of data supervised learning is carried out; and if the output information is inconsistent with the first service level information requirement of the first manager playing the role of identification, the neural network learning model adjusts itself until the output result of the neural network learning model is consistent with the first service level information requirement of the first manager playing the role of identification, and then the supervised learning of the next group of data is carried out. The neural network learning model is continuously corrected and optimized through training data, the accuracy of the neural network learning model for processing the information is improved through the process of supervised learning, and the technical effect that the first service level information of the first manager of each enterprise in the third enterprise library is more accurate is achieved.

Further, after the first big data cloud platform is established according to the first big data platform establishment instruction and the first intellectual property information of each enterprise in the third enterprise repository, the embodiment of the present application further includes:

step 1310: obtaining a first predetermined time interval;

step S1320: acquiring second intellectual property data through the first big data cloud platform according to the first preset time interval;

step S1330: and sending the second intellectual property data to the first manager.

Specifically, after the first big data cloud platform is established, in order to periodically obtain the latest intellectual property data, a first predetermined time interval may also be obtained, where the first predetermined time interval is a preset certain time to update the data in the first big data cloud platform, and the first predetermined time interval may be every day, every week, every month, or the like, and is not specifically set herein, and further according to the first predetermined time interval, second intellectual property data, that is, the latest intellectual property new dynamic information related to the industry, including design drawings, public selling products, production, and new research and development materials or research and development production methods, is collected by the first big data cloud platform, and at the same time, the second intellectual property data is sent to the first administrator, and by periodically updating and sending the intellectual property data of the first big data cloud platform to the administrator, the technical effects that managers can master the development trend of the industry in real time and can conveniently make correct planning on the development direction in the following seasons are achieved.

Further, the embodiment of the application further comprises:

step S1340: obtaining first planning drawing information sent by the first manager according to the first big data cloud platform;

step S1350: judging whether the first planning drawing information meets a preset production condition or not based on the first big data cloud platform;

step S1360: and if not, acquiring second reminding information and sending the second reminding information to the first manager.

Specifically, first plan drawing information sent by the first manager can be obtained according to the first big data cloud platform, the first plan drawing information is a newly designed design drawing of an enterprise company where the first manager is located, whether the first plan drawing information meets preset commissioning conditions is judged based on the first big data cloud platform, the first plan drawing information is compared with the existing design drawing of the first big data cloud platform, whether innovation or novelty is provided, whether rights and interests of other enterprises are infringed is judged, whether the first plan drawing information can be commissioned or not is judged according to a comparison result, if the first plan drawing information does not meet the preset commissioning conditions, second reminding information can be obtained, the second reminding information is that the first plan drawing information does not meet the preset commissioning conditions, and the first manager is sent with the second reminding information at the same time, redesigning and evaluating the first planning drawing information, and evaluating the planning drawing based on the big data cloud platform, so that the rights and interests of other enterprises are avoided, and the technical effect of innovativeness of the planning drawing is maintained.

To sum up, the enterprise intellectual property management method and system based on big data provided by the embodiment of the application have the following technical effects:

1. the enterprises which aggregate the preset attribute information and wish to join the intellectual property alliance platform and establish the enterprise database to establish the intellectual property alliance platform achieve the technical effects that managers can know the latest dynamic state of the industry in time, and meanwhile, management and maintenance of intellectual property information, authorization cooperation among the enterprises and the like can be provided for small and medium-sized enterprises.

2. Through uploading intellectual property data including design drawings, sold products, production, materials and the like to the first big data cloud platform, the first big data cloud platform is regularly updated and sent to management personnel, various kinds of information are effectively integrated, the platform is open and transparent, the technical effect that the management personnel master industry development trends in real time and correct planning is conveniently made for the development direction of follow-up enterprises is achieved.

Example two

Based on the same inventive concept as the method for managing enterprise intellectual property based on big data in the foregoing embodiment, the present invention further provides a system for managing enterprise intellectual property based on big data, as shown in fig. 2, the system includes:

the first obtaining unit 11: the first obtaining unit 11 is configured to obtain a first predetermined area;

the second obtaining unit 12: the second obtaining unit 12 is configured to obtain first enterprise repository information according to the first predetermined area, where the first enterprise repository includes a plurality of enterprises;

the third obtaining unit 13: the third obtaining unit 13 is configured to sequentially obtain first enterprise attribute information corresponding to each enterprise in the first enterprise repository;

the fourth obtaining unit 14: the fourth obtaining unit 14 is configured to obtain predetermined attribute information;

the fifth obtaining unit 15: the fifth obtaining unit 15 is configured to obtain, according to the predetermined attribute information and the first enterprise attribute information, a set of enterprises in the first enterprise repository that meet the predetermined attribute information;

the first establishing unit 16: the first establishing unit 16 is configured to establish second enterprise repository information according to a set of enterprises in the first enterprise repository that satisfy the predetermined attribute information;

sixth obtaining unit 17: the sixth obtaining unit 17 is configured to obtain a first big data platform establishment instruction;

the seventh obtaining unit 18: the seventh obtaining unit 18 is configured to obtain confirmation information from each enterprise in the second enterprise repository after sending the first big data platform establishment instruction to each enterprise in the second enterprise repository;

the second establishing unit 19: the second establishing unit 19 is configured to obtain a set of the confirmation information in the second enterprise repository according to the confirmation information, and establish third enterprise repository information;

the eighth obtaining unit 20: the eighth obtaining unit 20 is configured to obtain first intellectual property information of each enterprise in the third enterprise repository;

the third establishing unit 21: the third establishing unit 21 is configured to establish the first big data cloud platform according to the first big data platform establishing instruction and the first intellectual property information of each enterprise in the third enterprise repository, where the first big data cloud platform is an intellectual property alliance platform.

Further, the system further comprises:

a ninth obtaining unit: the ninth obtaining unit is configured to obtain first design drawing information of each enterprise in the third enterprise repository, where the first design drawing information is a design drawing of a public product;

a tenth obtaining unit: the tenth obtaining unit is configured to obtain first sold product information of each enterprise in the third enterprise repository, where the first sold product information is an open product;

a first judgment unit: the first judging unit is used for judging whether first production information exists in the third enterprise library, wherein the first production information comprises a first material and/or a first production method;

an eleventh obtaining unit: the eleventh obtaining unit is configured to obtain the first material, if present, and/or the first production method;

a twelfth obtaining unit: the twelfth obtaining unit is configured to obtain the first intellectual property information according to the first design drawing information, the first production information, the first material, and/or the first production method.

Further, the system further comprises:

a thirteenth obtaining unit: the thirteenth obtaining unit is configured to obtain first administrator information of each enterprise in the third enterprise repository;

a fourteenth obtaining unit: the fourteenth obtaining unit is configured to obtain first business level information of the first administrator information;

a fifteenth obtaining unit: the fifteenth obtaining unit is configured to obtain a predetermined traffic level capability;

a second judgment unit: the second judging unit is used for judging whether the first service level information meets the preset service level capability;

a sixteenth obtaining unit: the sixteenth obtaining unit is configured to, if the preset service level capability is not met, obtain first reminding information, and send the first reminding information to the first manager that does not meet the preset service level capability.

Further, the system further comprises:

a seventeenth obtaining unit: the seventeenth obtaining unit is used for obtaining a first test instruction;

an eighteenth obtaining unit: the eighteenth obtaining unit is configured to obtain a first test value after performing a service level test on each first administrator according to the first test instruction;

a nineteenth obtaining unit: the nineteenth obtaining unit is configured to obtain first professional information and first social attribute information of the first administrator of each enterprise in the third enterprise repository;

a twentieth obtaining unit: the twentieth obtaining unit is configured to obtain first business level information of the first administrator information according to the first test value, the first practitioner information, and the first social attribute information.

Further, the system further comprises:

a first input unit: the first input unit is configured to input the first test value, the first practitioner information, and the first social attribute information into a first neural network model, where the model is trained using multiple sets of training data, and each set of training data in the multiple sets includes: the first test value, the first practitioner information, the first social attribute information and identification information identifying first business level information of a first administrator;

a twenty-first obtaining unit: the twenty-first obtaining unit is configured to obtain output information of the model, where the output information includes a first result, and the first result is first business level information of a first manager of each enterprise in the third enterprise repository.

Further, the system further comprises:

a twenty-second obtaining unit: the twenty-second obtaining unit is configured to obtain a first predetermined time interval;

a first acquisition unit: the first acquisition unit is used for acquiring second intellectual property data through the first big data cloud platform according to the first preset time interval;

a first transmission unit: the first sending unit is used for sending the second intellectual property data to the first manager.

Further, the system further comprises:

a twenty-third obtaining unit: the twenty-third obtaining unit is used for obtaining first planning drawing information sent by the first manager according to the first big data cloud platform;

a third judging unit: the third judging unit is used for judging whether the first planning drawing information meets a preset production condition or not based on the first big data cloud platform;

a twenty-fourth obtaining unit: and the twenty-fourth obtaining unit is used for obtaining second reminding information if the first reminding information does not meet the requirement, and sending the second reminding information to the first manager.

Various changes and specific examples of the method for managing enterprise intellectual property based on big data in the first embodiment of fig. 1 are also applicable to the system for managing enterprise intellectual property based on big data in this embodiment, and through the foregoing detailed description of the method for managing enterprise intellectual property based on big data, those skilled in the art can clearly know the method for implementing the system for managing enterprise intellectual property based on big data in this embodiment, so for the brevity of the description, detailed description is not repeated.

EXAMPLE III

The electronic device of the embodiment of the present application is described below with reference to fig. 3.

Fig. 3 illustrates a schematic structural diagram of an electronic device according to an embodiment of the present application.

Based on the inventive concept of the enterprise intellectual property management method based on big data as in the previous embodiment, the present invention further provides an enterprise intellectual property management system based on big data, on which a computer program is stored, which when executed by a processor implements the steps of any one of the above-mentioned enterprise intellectual property management methods based on big data.

Where in fig. 3 a bus architecture (represented by bus 300), bus 300 may include any number of interconnected buses and bridges, bus 300 linking together various circuits including one or more processors, represented by processor 302, and memory, represented by memory 304. The bus 300 may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface 305 provides an interface between the bus 300 and the receiver 301 and transmitter 303. The receiver 301 and the transmitter 303 may be the same element, i.e., a transceiver, providing a means for communicating with various other apparatus over a transmission medium. The processor 302 is responsible for managing the bus 300 and general processing, and the memory 304 may be used for storing data used by the processor 302 in performing operations.

The embodiment of the application provides an enterprise intellectual property management method based on big data, wherein the method comprises the following steps: obtaining a first predetermined area; obtaining first enterprise library information according to the first preset area, wherein the first enterprise library comprises a plurality of enterprises; sequentially obtaining first enterprise attribute information corresponding to each enterprise in the first enterprise library; obtaining predetermined attribute information; acquiring a set of enterprises meeting the preset attribute information in the first enterprise library according to the preset attribute information and the first enterprise attribute information; establishing second enterprise repository information according to the set of enterprises meeting the preset attribute information in the first enterprise repository; obtaining a first big data platform establishment instruction; after the first big data platform establishing instruction is sent to each enterprise in the second enterprise library, obtaining confirmation information of each enterprise in the second enterprise library; acquiring a set of confirmation information in the second enterprise library according to the confirmation information, and establishing third enterprise library information; obtaining first intellectual property information of each enterprise in the third enterprise repository; and establishing the first big data cloud platform according to the first big data platform establishing instruction and the first intellectual property information of each enterprise in the third enterprise library, wherein the first big data cloud platform is an intellectual property alliance platform.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.

It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.