Personalized recommendation method based on group user behavior analysis

Abstract

The invention discloses a personalized recommendation method based on group user behavior analysis, which belongs to the technical field of computer network application and provides a personalized recommendation method based on group user interest change, wherein a recommendation list with higher accuracy is obtained rapidly and effectively by collecting temporary dynamic interest degree of a large number of users to a commodity; in addition, the effect of time factor to a user's interest degree is analyzed quantitatively; by combining the time from contacting goods to buy goods by public users and the distribution diagram of the number of users who buy the goods at different time sections, so the accuracy of recommendation is improved; and after fully analyzing the datum of users' behaviors and summarizing the interest of users, the interest correlation between the goods and users is calculated.

Description

technical field [0001] The invention belongs to the technical field of computer network applications, and more specifically relates to a personalized recommendation method based on group user behavior analysis. Background technique [0002] In recent years, with the vigorous development of e-commerce, the proportion of online consumption in the retail sales of commodities in the whole society is getting higher and higher. The huge shopping advantages provided by online shopping to consumers are mainly reflected in the breakthrough of time and space constraints, convenient shopping, more product choices, competitive prices, rich product information, personalization and customization. At the same time, compared with offline consumption, e-commerce platforms and advertisers can record users' browsing paths and purchase history more conveniently and accurately, thereby accumulating massive amounts of user behavior data. There are many types of user behaviors on the e-commerce p...

AI Technical Summary

Problems solved by technology

[0005] In view of the above defects or improvement needs of the prior art, the present invention provides a personalized recommendation method based on group user behavior analysis, aiming at the fact that the existing recommendation algorithm does not learn the knowledge of group user behavior, which leads to low recommendation accuracy and user Considering the problem of incomplete timing characteristics of interest degree, a set of personalized recommendation method based on group user interest changes is proposed, and a recommendation list with higher accuracy can be quickly and effectively obtained by aggregating the dynamic interest of a large number of individual users on products.

Images