NDLI: Distributed community detection in web-scale networks

Content Provider	IEEE Xplore Digital Library
Author	Ovelgonne, M.
Copyright Year	2013
Description	Author affiliation: UMIACS, Univ. of Maryland, College Park, MD, USA (Ovelgonne, M.)
Abstract	Partitioning large networks into smaller sub-networks (communities) is an important tool to analyze the structure of complex linked systems. In recent years, many in-memory community detection algorithms have been proposed for graphs with millions of edges. Analyzing massive graphs with billions of edges is impossible for existing algorithms. In this contribution, we show how to find community partitions of networks with billions of edges. Our approach is based on an ensemble learning scheme for community detection that provides a way to identify high quality partitions from an ensemble of partitions with lower quality. We present a pre-processing procedure for community detection algorithms that significantly decreases the problem size. After reducing the problem size, traditional non-distributed community detection algorithms can be applied. We implemented a weak but highly scalable label propagation algorithm on top of the distributed-computing framework Apache Hadoop. The evaluation of our implementation on a 50-node Hadoop cluster and with evaluation datasets up to 3.3 billion edges shows very good results with respect to clustering quality as well as scalability. For a smaller 260 million edge network, we show that our preprocessing can improve the results of the popular Louvain modularity clustering algorithm.
Sponsorship	IEEE Comput. Soc.
Starting Page	66
Ending Page	73
File Size	170128
Page Count	8
File Format	PDF
ISBN	9781450322409
DOI	10.1145/2492517.2492518
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-08-25
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	ACM and IEEE
Subject Keyword	Algorithm design and analysis Image edge detection Communities Clustering algorithms Graph Clustering Community Detection Vectors Partitioning algorithms Detection algorithms MapReduce Distributed Algorithms
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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