Knowledge graph-based collaborative recommendation method, apparatus and device, and storage medium

A technology of knowledge graph and recommendation method, applied in the fields of knowledge graph-based collaborative recommendation method, equipment and storage medium, and device, can solve problems such as cold start, and achieve the effect of simple steps, reasonable design, and reduced manpower
CN110472155APending Publication Date: 2019-11-19WUYI UNIV
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Patent Information

Authority / Receiving Office
CN ยท China
Current Assignee / Owner
WUYI UNIV
Publication Date
2019-11-19

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Abstract

The invention discloses a knowledge graph-based collaborative recommendation method, apparatus and device, and a storage medium, and the method comprises the following steps: obtaining score data of afirst target for an article; preprocessing the scoring data; constructing a knowledge graph related to the article based on the preprocessed scoring data, and obtaining an article label; obtaining the similarity between the first target and other targets according to the article label; and obtaining a similar target according to the similarity between the first target and other targets, and recommending preferred articles of the similar target to the first target. Compared with the prior art, the invention has the advantages that the steps are simple and convenient, the design is reasonable,expert annotation is not needed while the cold start problem is solved, the labor and time cost is greatly reduced, and favorite articles can be recommended to users according to the interests of theusers.
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Description

technical field

[0001] The present invention relates to the technical field of computer software, in particular to a collaborative recommendation method, device, device and storage medium based on knowledge graphs. Background technique

[0002] In the era of big data, people often fall into the predicament of information overload. At this time, the recommendation system came into being and was quickly applied successfully in music, movies, e-commerce and other fields. The recommendation system can accurately recommend music, movies or products that users are interested in, which not only helps users save a lot of time, but also efficiently sells products. Therefore, the recommendation system has received extensive attention from the industry and academia. At present, the recommendation system mainly adopts the content recommendation method and the collaborative recommendation method. The content recommendation method converts items into content vectors and then calculates th...

Claims

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