The App Recommendation Algorithm Based on Heterogeneous Network and Meta-path

Abstract

Abstract:

With the rapid development of mobile Internet, users usually download Apps from mobile application markets. On the one hand, in order to expand the influence, individual mobile application market faces the situation of recommending App to users and keeping them. On the other hand, for a user, in the face of millions of Apps from every application market, how to choose the Apps that they really like is an urgent issue. This paper proposes a meta-path-based App recommendation approach based on heterogeneous network analysis. Using the real dataset from Talking Data, we verify the effectiveness of the proposed algorithm. We also compare the recommendation results of the meta-path-based recommendation algorithm and several baseline algorithms, including user-based collaborative filtering recommendation algorithm, item-based collaborative filtering recommendation algorithm and bipartite graph based recommendation algorithm. Experiment results show that meta-path-based algorithm produces better performances than the baseline algorithms on MAP and MRR measures.

Key words: App, heterogeneous network, recommendation algorithm, meta-path

Jiang Yipan, Zhang Wen, Li Jian, Chen Jindong. The App Recommendation Algorithm Based on Heterogeneous Network and Meta-path[J]. , 2020, 32(4): 160-170.

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