SibRank: Signed Bipartite Network Analysis for Neighbor-based Collaborative Ranking
Social and Information Networks
2016-06-15 v2
Abstract
Collaborative ranking is an emerging field of recommender systems that utilizes users' preference data rather than rating values. Unfortunately, neighbor-based collaborative ranking has gained little attention despite its more flexibility and justifiability. This paper proposes a novel framework, called SibRank that seeks to improve the state of the art neighbor-based collaborative ranking methods. SibRank represents users' preferences as a signed bipartite network, and finds similar users, through a novel personalized ranking algorithm in signed networks.
Cite
@article{arxiv.1601.05575,
title = {SibRank: Signed Bipartite Network Analysis for Neighbor-based Collaborative Ranking},
author = {Bita Shams and Saman Haratizadeh},
journal= {arXiv preprint arXiv:1601.05575},
year = {2016}
}