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.