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arXiv · 1601.05575

SibRank: Signed Bipartite Network Analysis for Neighbor-based Collaborative Ranking

Bita Shams·Saman Haratizadeh
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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.

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Bita Shams, Saman Haratizadeh. 2016-01-21. SibRank: Signed Bipartite Network Analysis for Neighbor-based Collaborative Ranking. https://doi.org/10.1016/j.physa.2016.04.025

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