PathRank: A Novel Node Ranking Measure on a Heterogeneous Graph for Recommender Systems

Information

Title PathRank: A Novel Node Ranking Measure on a Heterogeneous Graph for Recommender Systems
Authors Sangkeun Lee, Sungchan Park, Minsuk Kahng, Sang-goo Lee
Year 2012 / 10
Keywords Graph, Network, Recommender systems, PageRank, Personalized PageRank, Heterogeneity, Flexibility, Ranking
Acknowledgement NRF
Publication Type International Conference
Publication Proceedings of the 21st ACM Conference on Information and Knowledge Management (CIKM 2012), pp. 1637-1641
Link doi

Abstract

In this paper, we present a novel random-walk based node ranking measure, PathRank, which is defined on a heterogeneous graph by extending the Personalized PageRank algorithm. Not only can our proposed measure exploit the semantics behind the different types of nodes and edges in a heterogeneous graph, but also it can emulate various recommendation semantics such as collaborative filtering, content- based filtering, and their combinations. The experimental results show that PathRank can produce more various and effective recommendation results compared to existing approaches.