Article recommendation method and device and computer storage medium

Abstract

The invention discloses an article recommendation method and device and a storage medium, and belongs to the field of information recommendation. The method comprises the following steps: determining first prediction scores of a plurality of articles through a collaborative filtering model according to article behavior data of a target user; determining k first articles from the plurality of articles according to the first prediction scores of the plurality of articles; determining first entity vectors of the k first articles according to the k first articles and the knowledge graph vector set; determining a second prediction score of the k first articles according to the first entity vectors of the k first articles and the article behavior data of the target user; and if a mean square error between the first prediction scores and the second prediction scores of the k first articles is smaller than or equal to an error threshold value, recommending the k first articles to the target user. According to the recommendation algorithm, on the basis of determining the similarity of the articles according to the behavior data of the articles, the similarity among the article attributes is fully considered, and the recommendation accuracy is further improved.

Description

technical field [0001] The present application relates to the field of information recommendation, in particular to an item recommendation method, device and computer storage medium. Background technique [0002] Currently, network platforms can provide users with online recommendation services for items such as news, commodities, pictures, videos, audios, documents, and the like. When a user browses, collects, or rates an item on the network platform, the server of the network platform will record the user’s item behavior data, mine user preferences based on the user’s item behavior data, and recommend items of interest to the user. [0003] In related technologies, a collaborative filtering recommendation algorithm is usually used to recommend items for users. Specifically, for the target user on the network platform, the item behavior data of the target user can be obtained, and then according to the item behavior data of the target user, the predicted scores of multiple...

AI Technical Summary

Problems solved by technology

[0005] The embodiment of the present application provides an item recommendation method, device, and storage medium, which can solve the problem of relatively one-sided analysis of item similarity and low recommendation accuracy existing in related technologies

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