1. BiRank: Towards Ranking on Bipartite Graphs.
- Author
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He, Xiangnan, Gao, Ming, Kan, Min-Yen, and Wang, Dingxian
- Subjects
- *
BIPARTITE graphs , *UBIQUITOUS computing , *GRAPH theory - Abstract
The bipartite graph is a ubiquitous data structure that can model the relationship between two entity types: for instance, users and items, queries and webpages. In this paper, we study the problem of ranking vertices of a bipartite graph, based on the graph's link structure as well as prior information about vertices (which we term a query vector). We present a new solution, BiRank, which iteratively assigns scores to vertices and finally converges to a unique stationary ranking. In contrast to the traditional random walk-based methods, BiRank iterates towards optimizing a regularization function, which smooths the graph under the guidance of the query vector. Importantly, we establish how BiRank relates to the Bayesian methodology, enabling the future extension in a probabilistic way. To show the rationale and extendability of the ranking methodology, we further extend it to rank for the more generic $n$
- Published
- 2017
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