Multi-platform integration method and device, electronic equipment and computer readable storage medium

Abstract

The invention relates to the technical field of multi-platform integration, and discloses a multi-platform integration method. Comprising a knowledge base integration method and an algorithm integration method. The knowledge base integration method comprises the steps that knowledge base sources needing to be integrated are acquired, entities in different knowledge bases are aligned through a multi-source knowledge base entity alignment algorithm of network semantic tags, and an integrated knowledge base is generated; performing data mining on the integrated knowledge base, and constructing a knowledge base graph; the algorithm integration method comprises the following steps: acquiring algorithms needing to be integrated, and integrating the algorithms of different platforms into the same database to generate an integrated database; the NoSQL database is used for storing the integrated database; the method has the advantages of reducing system complexity, improving user experience, improving system efficiency and enhancing knowledge sharing.

Description

Technical Field

[0001] The present invention relates to the technical field of multi-platform integration, and in particular to a multi-platform integration method, device, electronic device and computer-readable storage medium. Background Art

[0002] With the rapid development of artificial intelligence technology in recent years, more and more insurance companies have begun to introduce AI intelligent robot systems to improve customer service experience and work efficiency. However, the existing insurance industry customer service systems, intelligent robot systems and artificial intelligence platforms often have problems with multi-platform complexity and inability to integrate. Due to differences in data formats, knowledge bases, etc. between different systems, effective cross-platform collaboration and information sharing cannot be achieved, which has brought a lot of trouble to the operation and management of insurance companies.

[0003] The current insurance industry has the following problems:

[0004] Complex interactions across multiple platforms: The insurance industry usually has multiple independent platform systems, such as customer service systems, intelligent robot systems, AI smart assistant platforms, etc. There is a lack of unified standards and interaction mechanisms between these platforms, resulting in poor user experience and low efficiency during use.

[0005] Information islands: Each platform has its own independent knowledge base and lacks effective integration, resulting in the inability to share knowledge, duplicate construction, and ineffective use of information.

[0006] Complex and redundant systems: There are duplicate functions between different platform systems, resulting in high development and maintenance costs and low system efficiency.

[0007] Independence of algorithm models: The algorithm models used by various systems are mostly developed independently and cannot be effectively coordinated, resulting in waste of resources and duplication of functions.

[0008] Complex front-end interaction: Different systems have different front-end interaction methods, which brings a poor user experience.

[0009] In the prior art, the above problems are mainly solved by API interface integration and data warehouse integration. However, realizing data interaction between different platforms through API interface requires a lot of development work, and it is difficult to achieve deep integration of data between platforms. Integrating data from different platforms into a data warehouse is difficult to process real-time data, and cannot solve the differences in logic and functions between platforms.

[0010] Therefore, a multi-platform integration method, device, electronic device and computer-readable storage medium are provided to solve the above problems. Summary of the invention

[0011] The main purpose of the present invention is to solve the problems in the prior art that data interaction between different platforms is achieved through API interfaces, which requires a lot of development work and is difficult to achieve deep integration of data between platforms; integrating data from different platforms into a data warehouse is difficult to process real-time data, and cannot solve the differences in logic and functions between platforms.

[0012] A first aspect of the present invention provides a multi-platform integration method, the multi-platform integration method comprising:

[0013] Knowledge base integration methods and algorithm integration methods;

[0014] The knowledge base integration method comprises:

[0015] Obtain the knowledge base sources to be integrated, use the multi-source knowledge base entity alignment algorithm of network semantic tags to align the entities in different knowledge bases, and generate an integrated knowledge base;

[0016] Conduct data mining on the integrated knowledge base and construct a knowledge base graph;

[0017] The algorithm integration method comprises:

[0018] Obtain the algorithms that need to be integrated, integrate the algorithms of different platforms into the same database, and generate an integrated database;

[0019] Use NoSQL database to store the integrated database.

[0020] Optionally, it also includes a front-end page design integration method, and the front-end page design integration method includes:

[0021] Set up the AI ​​dialogue input interface, manual input interface and interface switching module on the front-end page.

[0022] Optionally, the knowledge base sources to be integrated include a customer service system knowledge base, an AI intelligent assistant platform knowledge base, and an intelligent robot knowledge base.

[0023] Optionally, the multi-source knowledge base entity alignment algorithm using network semantic tags to align entities in different knowledge bases includes:

[0024] Obtain the semantic labels of entities in the customer service system knowledge base, AI smart assistant platform knowledge base, and smart robot knowledge base respectively;

[0025] According to the semantic labels, it is determined whether the entities in the above three databases are the same entity. If so, the same entity is merged; if not, two different entities are retained.

[0026] Optionally, performing data mining on the integrated knowledge base to construct a knowledge base graph includes:

[0027] Mining structural models and association rules in the integrated knowledge base;

[0028] Based on the structural model and association rules, a graph representation of the knowledge base is constructed.

[0029] Optionally, the step of obtaining the algorithms to be integrated and integrating the algorithms of different platforms into the same database includes:

[0030] Obtain natural language processing algorithms, machine learning algorithms, and deep learning algorithms;

[0031] Integrate natural language processing algorithms, machine learning algorithms, and deep learning algorithms into the same database.

[0032] A second aspect of the present invention provides a multi-platform integration device, comprising:

[0033] Knowledge base integration module and algorithm integration module,

[0034] The knowledge base integration module includes:

[0035] An integrated knowledge base generation unit is used to obtain the knowledge base sources to be integrated, align entities in different knowledge bases using a multi-source knowledge base entity alignment algorithm with network semantic tags, and generate an integrated knowledge base;

[0036] A knowledge graph base construction unit is used to perform data mining on the integrated knowledge base and construct a knowledge base graph;

[0037] The algorithm integration module includes:

[0038] An integrated database generation unit is used to obtain algorithms that need to be integrated, integrate algorithms from different platforms into the same database, and generate an integrated database;

[0039] The data storage unit is used to store the integrated database using a NoSQL database.

[0040] A third aspect of the present invention provides an electronic device, the electronic device comprising a memory and at least one processor, the memory storing instructions;

[0041] The at least one processor calls the instructions in the memory to enable the electronic device to execute each step of the multi-platform integration method as described above.

[0042] A fourth aspect of the present invention provides a computer-readable storage medium, on which instructions are stored, and when the instructions are executed by a processor, the various steps of the multi-platform integration method described above are implemented.

[0043] The technical solution of the present invention provides a multi-platform integration method, which reduces system redundancy and development and maintenance costs by integrating multi-platform knowledge bases and algorithms; provides a unified interactive interface, and users do not need to switch between different platforms, making operation more convenient and the experience smoother; by integrating information, duplicate construction is avoided and the overall efficiency of the system is improved; information islands are broken, knowledge sharing and collaboration are achieved, and the efficiency of knowledge utilization is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 A flow chart of a knowledge base integration method in a multi-platform integration method provided by an embodiment of the present invention;

[0045] Figure 2 A flowchart of an algorithm integration method in a multi-platform integration method provided by an embodiment of the present invention;

[0046] Figure 3 A schematic diagram of the structure of a multi-platform integration device provided by an embodiment of the present invention;

[0047] Figure 4 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The embodiment of the present invention provides a multi-platform integration method, including a knowledge base integration method and an algorithm integration method; the knowledge base integration method includes: obtaining the knowledge base source to be integrated, using a multi-source knowledge base entity alignment algorithm of network semantic tags to align entities in different knowledge bases, and generating an integrated knowledge base; performing data mining on the integrated knowledge base to construct a knowledge base graph; the algorithm integration method includes: obtaining the algorithms to be integrated, integrating the algorithms of different platforms into the same database, and generating an integrated database; using a NoSQL database to store the integrated database. The present invention solves the problems in the prior art that data interaction between different platforms is achieved through an API interface, which requires a lot of development work and is difficult to achieve deep integration of data between platforms; integrating data from different platforms into a data warehouse is difficult to process real-time data, and cannot solve the differences in logic and functions between platforms.

[0049] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0050] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 -2. The first embodiment of the multi-platform integration method in the embodiment of the present invention includes:

[0051] Knowledge base integration methods and algorithm integration methods;

[0052] The knowledge base integration method comprises:

[0053] Obtaining knowledge base sources to be integrated, wherein the knowledge base sources to be integrated include a customer service system knowledge base, an AI intelligent assistant platform knowledge base, and an intelligent robot knowledge base;

[0054] Use a multi-source knowledge base entity alignment algorithm with network semantic labels to align entities in different knowledge bases; specifically, obtain semantic labels of entities in the customer service system knowledge base, AI intelligent assistant platform knowledge base, and intelligent robot knowledge base respectively; determine whether the entities in the above three databases are the same entity based on the semantic labels, and if so, merge the same entity; if not, retain two different entities;

[0055] Generate an integrated knowledge base;

[0056] Conduct data mining on the integrated knowledge base and construct a knowledge base graph, which specifically includes:

[0057] Mining structural models and association rules in the integrated knowledge base;

[0058] Based on the structural model and association rules, a graph representation of the knowledge base is constructed.

[0059] The algorithm integration method comprises:

[0060] Obtain the algorithms that need to be integrated, integrate the algorithms of different platforms into the same database, and generate an integrated database; specifically, it includes:

[0061] Obtain natural language processing algorithms, machine learning algorithms, and deep learning algorithms;

[0062] Integrate natural language processing algorithms, machine learning algorithms, and deep learning algorithms into the same database.

[0063] Use NoSQL database to store the integrated database; use NoSQL database to store the integrated knowledge base data. The database has high flexibility and high scalability and can effectively store and manage massive data.

[0064] See also Figure 1-2 The second embodiment of the multi-platform integration method in the embodiment of the present invention includes:

[0065] Knowledge base integration methods and algorithm integration methods;

[0066] The knowledge base integration method comprises:

[0067] Obtaining knowledge base sources to be integrated, wherein the knowledge base sources to be integrated include a customer service system knowledge base, an AI intelligent assistant platform knowledge base, and an intelligent robot knowledge base;

[0068] Use a multi-source knowledge base entity alignment algorithm with network semantic labels to align entities in different knowledge bases; specifically, obtain semantic labels of entities in the customer service system knowledge base, AI intelligent assistant platform knowledge base, and intelligent robot knowledge base respectively; determine whether the entities in the above three databases are the same entity based on the semantic labels, and if so, merge the same entity; if not, retain two different entities;

[0069] Generate an integrated knowledge base;

[0070] Conduct data mining on the integrated knowledge base and construct a knowledge base graph, which specifically includes:

[0071] Mining structural models and association rules in the integrated knowledge base;

[0072] Based on the structural model and association rules, a graph representation of the knowledge base is constructed.

[0073] The algorithm integration method comprises:

[0074] Obtain the algorithms that need to be integrated, integrate the algorithms of different platforms into the same database, and generate an integrated database; specifically, it includes:

[0075] Obtain natural language processing algorithms, machine learning algorithms, and deep learning algorithms;

[0076] Combine natural language processing, machine learning, and deep learning algorithms into a single database.

[0077] Use NoSQL database to store the integrated database; use NoSQL database to store the integrated knowledge base data. The database has high flexibility and high scalability and can effectively store and manage massive data.

[0078] It also includes a front-end page design integration method, which includes:

[0079] Set up the AI ​​dialogue input interface, manual input interface and interface switching module on the front-end page; specifically, design a unified front-end interface to integrate customer service, smart robots, AI smart assistants and other functions into the same interface; realize AI-human dialogue form, so that users can directly communicate with the AI ​​smart robot without manual input; realize manual input mode, so that users can switch to manual input mode according to actual needs; design a switch button to facilitate users to switch between AI-human dialogue mode and manual input mode.

[0080] The above describes the multi-platform integration method in the embodiment of the present invention. The following describes the multi-platform integration device in the embodiment of the present invention. Figure 3 In the embodiment of the present invention, the multi-platform integration device includes:

[0081] Knowledge base integration module and algorithm integration module,

[0082] The knowledge base integration module includes:

[0083] An integrated knowledge base generation unit is used to obtain the knowledge base sources to be integrated, align entities in different knowledge bases using a multi-source knowledge base entity alignment algorithm with network semantic tags, and generate an integrated knowledge base;

[0084] A knowledge graph base construction unit is used to perform data mining on the integrated knowledge base and construct a knowledge base graph;

[0085] The algorithm integration module includes:

[0086] An integrated database generation unit is used to obtain algorithms that need to be integrated, integrate algorithms from different platforms into the same database, and generate an integrated database;

[0087] The data storage unit is used to store the integrated database using a NoSQL database.

[0088] above Figure 3 The multi-platform integration device in the embodiment of the present invention is described in detail from the perspective of modular functional entities, and the electronic device in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0089] Figure 47 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. The electronic device 700 may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 710 (for example, one or more processors) and a memory 720, and one or more storage media 730 (for example, one or more mass storage devices) storing application programs 733 or data 732. Among them, the memory 720 and the storage medium 730 can be temporary storage or permanent storage. The program stored in the storage medium 730 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations in the electronic device 700. Furthermore, the processor 710 can be configured to communicate with the storage medium 730 to execute a series of instruction operations in the storage medium 730 on the electronic device 700.

[0090] The electronic device 700 may also include one or more power supplies 740, one or more wired or wireless network interfaces 750, one or more input and output interfaces 750, and / or one or more operating systems 731, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, etc. It will be appreciated by those skilled in the art that Figure 4 The structure of the electronic device shown does not constitute a limitation on the electronic device, and may include more or less components than shown in the figure, or combine some components, or arrange the components differently.

[0091] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium, and when the instructions are executed on a computer, the computer executes the steps of the multi-platform integration method.

[0092] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described system, device, or unit can refer to the corresponding process in the aforementioned method embodiment and will not be repeated here.

[0093] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.

[0094] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A multi-platform integration method, characterized in that: The multi-platform integration method comprises: Knowledge base integration methods and algorithm integration methods; The knowledge base integration method comprises: Obtain the knowledge base sources to be integrated, use the multi-source knowledge base entity alignment algorithm of network semantic tags to align the entities in different knowledge bases, and generate an integrated knowledge base; Conduct data mining on the integrated knowledge base and construct a knowledge base graph; The algorithm integration method comprises: Obtain the algorithms that need to be integrated, integrate the algorithms of different platforms into the same database, and generate an integrated database; Use NoSQL database to store the integrated database.

2. The multi-platform integration method according to claim 1, characterized in that: It also includes a front-end page design integration method, which includes: Set up the AI ​​dialogue input interface, manual input interface and interface switching module on the front-end page.

3. The multi-platform integration method according to claim 2, characterized in that: The knowledge base sources that need to be integrated include the customer service system knowledge base, the AI ​​smart assistant platform knowledge base and the intelligent robot knowledge base.

4. The multi-platform integration method according to claim 3, characterized in that: The multi-source knowledge base entity alignment algorithm using network semantic tags to align entities in different knowledge bases includes: Obtain the semantic labels of entities in the customer service system knowledge base, AI smart assistant platform knowledge base, and smart robot knowledge base respectively; According to the semantic labels, it is determined whether the entities in the above three databases are the same entity. If so, the same entity is merged; if not, two different entities are retained.

5. The multi-platform integration method according to claim 4, characterized in that: The data mining of the integrated knowledge base and the construction of the knowledge base graph include: Mining structural models and association rules in the integrated knowledge base; Based on the structural model and association rules, a graph representation of the knowledge base is constructed.

6. The multi-platform integration method according to claim 5, characterized in that: The step of obtaining the algorithms to be integrated and integrating the algorithms of different platforms into the same database includes: Obtain natural language processing algorithms, machine learning algorithms, and deep learning algorithms; Integrate natural language processing algorithms, machine learning algorithms, and deep learning algorithms into the same database.

7. A multi-platform integration device, characterized in that: include: Knowledge base integration module and algorithm integration module, The knowledge base integration module includes: An integrated knowledge base generation unit is used to obtain the knowledge base sources to be integrated, align entities in different knowledge bases using a multi-source knowledge base entity alignment algorithm with network semantic tags, and generate an integrated knowledge base; A knowledge graph base construction unit is used to perform data mining on the integrated knowledge base and construct a knowledge base graph; The algorithm integration module includes: An integrated database generation unit is used to obtain algorithms that need to be integrated, integrate algorithms from different platforms into the same database, and generate an integrated database; The data storage unit is used to store the integrated database using a NoSQL database.

8. An electronic device, comprising a memory and at least one processor, wherein instructions are stored in the memory; The at least one processor calls the instructions in the memory to enable the electronic device to execute each step of the multi-platform integration method as described in any one of claims 1 to 6.

9. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by a processor, the steps of the multi-platform integration method according to any one of claims 1 to 6 are implemented.

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