B-Rank: A top N Recommendation Algorithm

Marcel Blattner

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arXiv · 0908.2741

B-Rank: A top N Recommendation Algorithm

Marcel Blattner

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Abstract

In this paper B-Rank, an efficient ranking algorithm for recommender systems, is proposed. B-Rank is based on a random walk model on hypergraphs. Depending on the setup, B-Rank outperforms other state of the art algorithms in terms of precision, recall (19% - 50%), and inter list diversity (20% - 60%). B-Rank captures well the difference between popular and niche objects. The proposed algorithm produces very promising results for sparse and dense voting matrices. Furthermore, a recommendation list update algorithm is introduced,to cope with new votes. This technique significantly reduces computational complexity. The implementation of the algorithm is simple, since B-Rank needs no parameter tuning.

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Marcel Blattner. 2009-08-19. B-Rank: A top N Recommendation Algorithm. https://arxiv.org/abs/0908.2741

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