Session-based Recommendation Based on Long-term and Short-term Interest Incorporating Social Information

Xue Li; Jun Zhou; Chenxi Qu; Dajun Zhang

doi:10.54097/ee4j9y9m

Authors

Xue Li
Jun Zhou
Chenxi Qu
Dajun Zhang

DOI:

https://doi.org/10.54097/ee4j9y9m

Keywords:

Session Recommendation, Short-term and Long-term Interest, Social Relationship, Graph Attention Network

Abstract

In session-based recommendation systems, user interests are dynamic and purchasing actions are often influenced by both long-term and short-term interest preferences. However, user interests are not solely influenced by the users themselves but also by other external factors, such as social connections. To address these issues, a method utilizing a Graph Attention Network is proposed, which effectively integrates both the long-term and short-term interests of users and their friends. Experiments on the Douban and Delicious datasets demonstrate that the proposed algorithm outperforms baseline models.

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