@inproceedings{9ad8c7b8dba942e59c6566ae39bc2f83,
title = "On finding the maximum edge biclique in a bipartite graph: A subspace clustering approach",
abstract = "Bipartite graphs have been proven useful in modeling a wide range of relationship networks. Finding the maximum edge biclique within a bipartite graph is a well-known problem in graph theory and data mining, with numerous real-world applications across different domains. We propose a probabilistic algorithm for finding the maximum edge biclique using a Monte Carlo subspace clustering approach. Extensive experimentation with both artificial and real-world datasets shows that the algorithm is significantly better than the state-of-the-art technique. We prove that there are solid theoretical reasons for the algorithm's efficacy that manifest in a polynomial complexity of time and space.",
keywords = "Biclique, Data mining, Graph mining, Maximum edge bipartite subgraph, Subspace clustering",
author = "Eran Shaham and Honghai Yu and Li, {Xiao Li}",
note = "Publisher Copyright: Copyright {\textcopyright} by SIAM.; 16th SIAM International Conference on Data Mining 2016, SDM 2016 ; Conference date: 05-05-2016 Through 07-05-2016",
year = "2016",
month = jan,
day = "1",
language = "English",
series = "16th SIAM International Conference on Data Mining 2016, SDM 2016",
publisher = "Society for Industrial and Applied Mathematics Publications",
pages = "315--323",
editor = "Venkatasubramanian, {Sanjay Chawla} and Wagner Meira",
booktitle = "16th SIAM International Conference on Data Mining 2016, SDM 2016",
address = "United States",
}