A method and system for querying and recommending information resources based on knowledge graphs

Abstract

The present invention proposes a method and system for querying and recommending information resources based on knowledge graphs. The method first preprocesses the knowledge graphs, uses representation learning methods to map the knowledge graphs into low-dimensional dense vector spaces, and obtains vector representations of entities ; Then calculate the user's interest in information resources according to the user's historical behavior, and construct a user interest model by combining the vectorized representation of information resources and the user's interest in information resources; by calculating the similarity between resources and resources, users and resources To achieve accurate recommendation of information resources. The present invention combines knowledge map representation learning with user interest models to provide users with personalized services, taking into account the internal relationship of knowledge and user interests, and recommending resources that are related to the query content and in line with the user's interests according to the name of the resource input by the user. Information resources make personalized query and recommendation 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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