@inproceedings{91b1629df1bd4c28a0d24c9cc8903ac8,
title = "The (un)supervised detection of overlapping communities as well as hubs and outliers via (Bayesian) NMF",
abstract = "The detection of communities in various networks has been considered by many researchers. Moreover, it is preferable for a community detection method to detect hubs and out- liers as well. This becomes even more interesting and chal- lenging when taking the unsupervised assumption, that is, we do not assume the prior knowledge of the number K of communities. In this poster, we define a novel model to identify overlapping communities as well as hubs and out- liers. When K is given, we propose a normalized symmetric nonnegative matrix factorization algorithm to learn the pa- rameters of the model. Otherwise, we introduce a Bayesian symmetric nonnegative matrix factorization to learn the pa- rameters of the model, while determining K.Our experiment indicates its superior performance on various networks.",
keywords = "(Bayesian) NMF, Community, Hubs, Outliers",
author = "Xiaochun Cao and Xiao Wang and Di Jin and Yixin Cao and Dongxiao He",
note = "Publisher Copyright: {\textcopyright} Copyright 2014 by the International World Wide Web Conferences Steering Committee.; 23rd International Conference on World Wide Web, WWW 2014 ; Conference date: 07-04-2014 Through 11-04-2014",
year = "2014",
month = apr,
day = "7",
doi = "10.1145/2567948.2577307",
language = "英语",
series = "WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web",
publisher = "Association for Computing Machinery, Inc",
pages = "233--234",
booktitle = "WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web",
}