Item recommendation method, apparatus, computer apparatus and storage medium

Abstract

Embodiments of the present application disclose an item recommendation method, apparatus, computer device, and storage medium. The method includes: determining a target user group from a plurality ofuser groups according to a score vector of the target user, and then calculating a similarity value between the target user and each user in the user group to which the target user belongs; Determining a similar user of the target user according to the similarity value; Obtaining items scored by similar users but not scored by target users as recommendation items and generating a first item recommendation table according to the recommendation items; According to the similarity value between the target user and the similar user, the scoring value of each recommended item by the similar user andthe corresponding time attenuation factor, calculating the scoring value of each recommendation item according to the preset calculation formula; sorting a plurality of recommendation items accordingto a preset sorting rule according to an item score value to generate a second item recommendation table and push to a target user. This method can improve the accuracy of item recommendation and effectively avoid the lag problem of recommended projects.

Description

technical field [0001] The present application relates to the field of computer technology, in particular to an item recommendation method, device, computer equipment and storage medium. Background technique [0002] The recommendation system is an intelligent agent system proposed to solve the problem of information overload, which can automatically recommend resources that meet their interests, preferences or needs from a large amount of information to users. With the rapid development of the Internet, recommender systems have been applied in various fields, especially in e-commerce websites and other fields. [0003] Collaborative filtering algorithms are commonly used algorithms in recommendation systems, including user-based collaborative filtering algorithms and item-based collaborative filtering algorithms. However, at present, whether it is user-based or item-based collaborative filtering algorithm, there is a problem that the recommended items are outdated or laggi...

AI Technical Summary

Problems solved by technology

However, at present, both user-based and item-based collaborative filtering algorithms have the problem that the recommended items are outdated or lagging behind. The target users may have been interested in the recommended items, but they are no longer interested. This not only reduces the accuracy of pushing items, but also brings bad user experience to users

Images