Recommendation information determination method and server

Abstract

The invention discloses a recommendation information determination method and a server. By combining the attribute information of the user and the interaction information between the users, the walking probability of random walking on the social network is set, the influence of the attribute information and the interaction information on the walking probability is fully considered, the recommendation node is constructed based on more comprehensive information, and a more accurate recommendation result can be obtained. The method comprises the steps of obtaining a relation structure of a socialnetwork; determining node characteristic values and edge characteristic values according to the relation structure of the social network; determining a walking probability according to the node characteristic values and the edge characteristic values, the walking probability representing the walking probability of each node in the relation structure of the social network; acquiring a walking pathin a relation structure of the social network according to the walking probability; and determining a first recommendation node set according to the walking path, wherein the recommendation node setcomprises at least one node corresponding to the walking path.

Description

technical field [0001] The present application relates to the field of Internet technologies, and in particular to a method and server for determining recommended information. Background technique [0002] With the development of Internet technology, social networks have developed rapidly in recent years and have attracted more and more people's attention. Friend recommendation is an important function in social networks. Many social applications and games with social network services rely on recommending friends for users to attract users and enhance user stickiness. [0003] At present, the friend recommendation technology on social networks generally faces the challenge of data sparsity. Although the existing friend recommendation method based on the random walk strategy can effectively deal with the problem of sparse user data, the friend recommendation method based on the random walk strategy is mainly Searching for potential friend relationships based on the social re...

AI Technical Summary

Problems solved by technology

[0003] At present, friend recommendation technology on social networks generally faces the challenge of data sparsity. Although the existing friend recommendation method based on random walk strategy can effectively deal with the problem of sparse user data, the friend recommendation method based on random walk strategy is mainly According to the social relationship between users to search for potential friend relationships, the effect of friend recommendation is poor, and it is difficult to provide users with accurate friend recommendation services

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