Optimal compression for bipartite networks

Shuhong Huang, Xiangrong Wang, Liyang Peng, Jiarong Xie, Jiachen Sun and Yanqing Hu

Chaos, Solitons & Fractals, 2021, vol. 151, issue C

Abstract: Bipartite network is crucial for recommendation systems as user-product behaviors are thoroughly described by bipartite interactions. Almost all of the state-of-the-art network compression algorithms are designed for general networks without harnessing the unique bipartite structure. Until 2017, Basu and Varshney proposed a compression algorithm, BSZIP, selectively for bipartite networks. However, the performance of this algorithm is not clear. Here, we derive the structural entropy which is equivalent to the compression limit for unlabeled random bipartite networks. Theoretically, we show that BSZIP algorithm asymptotically achieves the analytical limit.

Keywords: Network compression; Network entropy; Theoretical compression limit; Recommendation systems (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:151:y:2021:i:c:s0960077921005610

DOI: 10.1016/j.chaos.2021.111207

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