Commodity information retrieval method, system and equipment based on large model knowledge base and storage medium

Abstract

The invention discloses a commodity information retrieval method, system and device based on a large model knowledge base and a storage medium. The method comprises the steps that a large amount of data is collected to train a universal large model, and parameters are extracted; creating different industrial knowledge bases according to an industrial chain; storing the product knowledge of each enterprise into a corresponding industry knowledge base; and correspondingly binding the parameters with the industrial knowledge base. According to the method, the information retrieval precision is improved, and the search response content is enriched.

Description

Technical Field

[0001] The present invention relates to the technical field of commodity information retrieval, and in particular to a commodity information retrieval method, system, device and storage medium based on a large model knowledge base. Background Art

[0002] With the deepening of digital transformation, industrial e-commerce platforms aggregate product information of enterprises in various industrial chains and provide services for matchmaking transactions. Searching for business opportunity information on the platform is an indispensable application. Currently, searches are mainly conducted through keyword searches. However, in the industrial field, the names of products are diverse, and aliases within a small range are everywhere; keyword searches for such personalized names are difficult to retrieve, and they also lack the flexibility of natural language searches. This will result in many business opportunity information not being retrieved, reducing the transaction completion rate. Summary of the invention

[0003] In view of the shortcomings existing in the above problems, the present invention provides a commodity information retrieval method, system, device and storage medium based on a large model knowledge base.

[0004] To achieve the above object, the present invention provides a commodity information retrieval method based on a large model knowledge base, comprising:

[0005] Collect a large amount of data to train a general large model and extract parameters;

[0006] Create different industry knowledge bases according to the industrial chain;

[0007] Storing the product knowledge of each enterprise into the corresponding industry knowledge base;

[0008] The parameters are correspondingly bound to the industry knowledge base.

[0009] Preferably, the product knowledge is stored in the corresponding industry knowledge base in the form of FAQ template or word template.

[0010] Preferably, the parameters are flexibly defined according to each industrial chain template and are correspondingly bound to the industrial knowledge base.

[0011] Preferably, the input parameters are input into the general macromodel and the search results are displayed on the interface.

[0012] The present invention also provides a commodity information retrieval system based on a large model knowledge base, comprising:

[0013] The training module is used to collect a large amount of data to train a general large model and extract parameters;

[0014] Creation module, used to create different industry knowledge bases according to the industrial chain;

[0015] A storage module is used to store the product knowledge of each enterprise into the corresponding industry knowledge base;

[0016] The binding module is used to bind the parameters to the industry knowledge base.

[0017] The present invention also provides a device, comprising at least one processing unit and at least one storage unit, wherein the storage unit stores a computer program, and when the program is executed by the processing unit, the processing unit executes the above method.

[0018] The present invention also provides a storage medium storing a computer program executable by an electronic device, and when the program runs on the electronic device, the electronic device executes the above method.

[0019] Compared with the prior art, the present invention has the following beneficial effects:

[0020] The present invention improves the accuracy of information retrieval and enriches the search response content. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a flow chart of the commodity information retrieval method based on the large model knowledge base of the present invention. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] Reference Figure 1 The present invention provides a commodity information retrieval method based on a large model knowledge base, comprising:

[0024] Collect a large amount of data to train a general large model and extract parameters;

[0025] Create different industry knowledge bases according to the industrial chain;

[0026] Store the product knowledge of each enterprise in the corresponding industry knowledge base in the form of FAQ template or word template;

[0027] Bind the parameters to the industry knowledge base. The parameters are flexibly defined according to each industry chain template and bound to the industry knowledge base.

[0028] Specifically, the search response API interface is defined, and the parameter fields are flexibly defined according to the templates of each industrial chain, and are bound to the large model knowledge base accordingly. When the searcher enters the search conditions, the front-end application will display the API return results on the interface.

[0029] The present invention mainly uses the large model knowledge base to search. Different knowledge bases are formed for different industrial fields. In this way, by searching the relevant content of the knowledge base, the search needs can be effectively understood, and then the powerful summarization ability of the large model is used to embed key items and links into the reply. Provide more accurate, extensive and richer replies to the searcher.

[0030] The present invention also provides a commodity information retrieval system based on a large model knowledge base, comprising:

[0031] The training module is used to collect a large amount of data to train a general large model and extract parameters;

[0032] Creation module, used to create different industry knowledge bases according to the industrial chain;

[0033] The storage module is used to store the product knowledge of each enterprise into the corresponding industry knowledge base;

[0034] The binding module is used to bind the parameters to the corresponding industry knowledge base.

[0035] The present invention also provides a device, comprising at least one processing unit and at least one storage unit, wherein the storage unit stores a computer program, and when the program is executed by the processing unit, the processing unit executes the above method.

[0036] The present invention also provides a storage medium storing a computer program executable by an electronic device. When the program runs on the electronic device, the electronic device executes the above method.

[0037] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A commodity information retrieval method based on a large model knowledge base, characterized in that: include: Collect a large amount of data to train a general large model and extract parameters; Create different industry knowledge bases according to the industrial chain; Storing the product knowledge of each enterprise into the corresponding industry knowledge base; The parameters are correspondingly bound to the industry knowledge base.

2. The commodity information retrieval method based on a large model knowledge base according to claim 1 is characterized in that: The product knowledge is stored in the corresponding industry knowledge base in the form of FAQ template or word template.

3. The commodity information retrieval method based on a large model knowledge base according to claim 2 is characterized in that: The parameters are flexibly defined according to each industrial chain template and are bound to the industrial knowledge base.

4. The commodity information retrieval method based on a large model knowledge base according to claim 3 is characterized in that: Input parameters are input into the general macro model, and the search results are displayed on the interface.

5. A commodity information retrieval system based on a large model knowledge base, characterized in that: include: The training module is used to collect a large amount of data to train a general large model and extract parameters; Creation module, used to create different industry knowledge bases according to the industrial chain; A storage module is used to store the product knowledge of each enterprise into the corresponding industry knowledge base; The binding module is used to bind the parameters to the industry knowledge base.

6. A device, characterized in that: The method comprises at least one processing unit and at least one storage unit, wherein the storage unit stores a computer program, and when the program is executed by the processing unit, the processing unit executes the method according to any one of claims 1 to 4.

7. A storage medium, characterized in that: It stores a computer program executable by an electronic device. When the program runs on the electronic device, the electronic device executes the method according to any one of claims 1 to 4.

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