2009 ConstantFactorApproximationAlgo
- (Tantipathananandh & Berger-Wolf, 2009) ⇒ Chayant Tantipathananandh, and Tanya Berger-Wolf. (2009). “Constant-factor Approximation Algorithms for Identifying Dynamic Communities.” In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2009). doi:10.1145/1557019.1557110
Subject Headings: Maximum Weighted Bipartite Matching.
Notes
- Categories and Subject Descriptors: F.2.0 Analysis of Algorithms and Problem Complexity: General.
- General Terms: Algorithms.
Cited By
- http://scholar.google.com/scholar?q=%22Constant-factor+approximation+algorithms+for+identifying+dynamic+communities%22+2009
- http://portal.acm.org/citation.cfm?doid=1557019.1557110&preflayout=flat#citedby
Quotes
Author Keywords
Approximation Algorithms, Community Identification, Dynamic Social Networks.
Abstract
We propose two approximation algorithms for identifying communities in dynamic social networks. Communities are intuitively characterized as unusually densely knit subsets of a social network. This notion becomes more problematic if the social interactions change over time. Aggregating social networks over time can radically misrepresent the existing and changing community structure. Recently, we have proposed an optimization-based framework for modeling dynamic community structure. Also, we have proposed an algorithm for finding such structure based on maximum weight bipartite matching. In this paper, we analyze its performance guarantee for a special case where all actors can be observed at all times. In such instances, we show that the algorithm is a small constant factor approximation of the optimum. We use a similar idea to design an approximation algorithm for the general case where some individuals are possibly unobserved at times, and to show that the approximation factor increases twofold but remains a constant regardless of the input size. This is the first algorithm for inferring communities in dynamic networks with a provable approximation guarantee. We demonstrate the general algorithm on real data sets. The results confirm the efficiency and effectiveness of the algorithm in identifying dynamic communities.
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Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
---|---|---|---|---|---|---|---|---|---|---|
2009 ConstantFactorApproximationAlgo | Chayant Tantipathananandh Tanya Berger-Wolf | Constant-factor Approximation Algorithms for Identifying Dynamic Communities | KDD-2009 Proceedings | 10.1145/1557019.1557110 | 2009 |