NDLI: Scalable Flow-Based Community Detection for Large-Scale Network Analysis

Content Provider	IEEE Xplore Digital Library
Author	Seung-Hee Bae Halperin, D. West, J. Rosvall, M. Howe, B.
Copyright Year	2013
Description	Author affiliation: Dept. of Phys., Umea Univ., Umea, Sweden (Rosvall, M.) \|\| Dept. of Comput. Sci. & Eng., Univ. of Washington, Seattle, WA, USA (Seung-Hee Bae; Halperin, D.; Howe, B.) \|\| Inf. Sch., Univ. of Washington, Seattle, WA, USA (West, J.)
Abstract	Community-detection is a powerful approach to uncover important structures in large networks. Since networks often describe flow of some entity, flow-based community-detection methods are particularly interesting. One such algorithm is called Info map, which optimizes the objective function known as the map equation. While Info map is known to be an effective algorithm, its serial implementation cannot take advantage of multicore processing in modern computers. In this paper, we propose a novel parallel generalization of Info map called Relax Map. This algorithm relaxes concurrency assumptions to avoid lock overhead, achieving 70% parallel efficiency in shared-memory multicore experiments while exhibiting similar convergence properties and finding similar community structures as the serial algorithm. We evaluate our approach on a variety of real graph datasets as well as synthetic graphs produced by a popular graph generator used for benchmarking community detection algorithms. We describe the algorithm, the experiments, and some emerging research directions in high-performance community detection on massive graphs.
Sponsorship	Toshiba
Starting Page	303
Ending Page	310
File Size	851303
Page Count	8
File Format	PDF
e-ISBN	9781479931422
DOI	10.1109/ICDMW.2013.138
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Infomap Heuristic algorithms Communities Clustering algorithms Community Detection Benchmark testing The map equation Mathematical model Parallel algorithms Equations
Content Type	Text
Resource Type	Article

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