Information resource query recommendation method and system based on knowledge graph

Abstract

The invention provides an information resource query recommendation method and system based on a knowledge graph, and the method comprises the steps: carrying out the preprocessing of the knowledge graph, enabling the knowledge graph to be mapped to a low-dimensional dense vector space through employing a representation learning method, and obtaining the vector representation of an entity; calculating the interest degree of the user in the information resource according to the historical behavior of the user, and constructing a user interest model by combining the vectorized representation ofthe information resource and the interest degree of the user in the information resource; achieving accurate recommendation of the information resources is achieved by calculating the similarity between the resources and the similarity between the users and the resources. According to the invention, the knowledge graph representation learning is combined with the user interest model to provide personalized service for the user; according to the method, the internal relation of knowledge and the interest of the user are considered, and the information resources related to the query content andconforming to the interest of the user are recommended to the user according to the queried resource name input by the user, so that the personalized query recommendation is more professional and targeted.

Description

technical field [0001] The present invention relates to the technical field of knowledge graph and recommendation, in particular to a method and system for querying and recommending information resources based on knowledge graph. Background technique [0002] In recent years, the vigorous development of information technology has driven the pace of informatization in all walks of life. The Internet, Internet of Things, cloud computing, etc. have gradually integrated into people's daily life, which has brought about explosive growth of data. The huge information resource library provides users with rich information, but it also brings the problem of resource overload, which makes users spend a lot of time in selecting the information resources they are interested in. The personalized query recommendation based on the user's historical behavior data can effectively alleviate the problem of resource overload. [0003] The recommendation system is one of the effective means to ...

AI Technical Summary

Problems solved by technology

[0006] At present, there have been some researches on recommendation methods based on knowledge graphs, such as path-based recommendation methods, which need to construct a specific path connecting two entities, but the method of manually constructing paths is difficult to reach the optimum in practice; graph-based algorithms The recommendation method intuitively utilizes the knowledge graph as a feature of the semantic network graph, and uses algorithms such as random walk to sample nodes in the graph, but the graph algorithm has poor portability and high computational complexity. When faced with a large knowledge graph, it is difficult to achieve real-time calculate

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