NDLI: A new label propagation with dams

Content Provider	IEEE Xplore Digital Library
Author	Attal, Jean-Philippe Malek, Maria
Copyright Year	2015
Description	Author affiliation: EISTI: Ecole Internationale des Sciences du Traitement de l'Information, Cergy-France 95000 Laboratoire Quartz (Malek, Maria) \|\| EISTI: Ecole Internationale des Sciences du Traitement de l'Information Cergy-France 95000 Laboratoire Quartz, ETIS-ENSEA Universite de Cergy-Pontoise CNRS France (Attal, Jean-Philippe)
Abstract	Label propagation is one of the fastest methods for community detection, with a near linear time complexity. It's a local method, where each node interacts with its neighbourhood to change its own label. Unfortunately, this method has two major drawbacks. The first is a bad propagation which can lead to obtain huge communities without sense (monster communities problem). The second is the instability of the method. Each trial of a label propagation algorithm gives rarely the same result. In this paper, we propose to do a study on the label propagation by putting artificial dams on edges of some networks in order to limit the propagation and to observe if this can lead to better results. We then apply an existing method based on a co-occurrence frequency matrix in order to stabilise the algorithm.
Starting Page	1292
Ending Page	1299
File Size	398976
Page Count	8
File Format	PDF
ISBN	9781450338547
DOI	10.1145/2808797.2808826
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-25
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Association for Computing Machinery, Inc. (ACM)
Subject Keyword	Algorithm design and analysis Image edge detection Social network services Complexity theory Partitioning algorithms Detection algorithms Standards
Content Type	Text
Resource Type	Article

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