Journal ArticleDOI
Fuzzy-rough community in social networks
Suman Kundu,Sankar K. Pal +1 more
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TLDR
Experimental results on benchmark data show the superiority of the proposed community detection algorithm compared to other well known methods, particularly when the network contains overlapping communities.About:
This article is published in Pattern Recognition Letters.The article was published on 2015-12-01. It has received 47 citations till now. The article focuses on the topics: Node (networking) & Fuzzy logic.read more
Citations
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Proceedings Article
On Network-Aware Clustering of Web Clients
TL;DR: Clusters---a grouping of clients that are close together topologically and likely to be under common administrative control are introduced, using a ``network-aware" method, based on information available from BGP routing table snapshots.
Journal ArticleDOI
Towards felicitous decision making
TL;DR: An overview on Big Data is presented including four issues, namely: concepts, characteristics and processing paradigms of Big data; the state-of-the-art techniques for decision making in Big Data; felicitous decision making applications of Big Data in social science; and the current challenges ofBig Data as well as possible future directions.
Journal ArticleDOI
An overview on the roles of fuzzy set techniques in big data processing: Trends, challenges and opportunities
TL;DR: Fuzzy sets have been employed for big data processing due to their ability to represent and quantify aspects of uncertainty as discussed by the authors, which can result in informative, intelligent and relevant decision making completed in various areas, such as medical and healthcare, business, management and government.
Journal ArticleDOI
CDLIB : a python library to extract, compare and evaluate communities from complex networks
TL;DR: The aim of CDlib is to allow easy and standardized access to a wide variety of network clustering algorithms, to evaluate and compare the results they provide, and to visualize them.
Posted Content
An Overview on the Roles of Fuzzy Set Techniques in Big Data Processing: Trends, Challenges and Opportunities
TL;DR: A critical review of the existing problems and discussion of the current challenges of big data, which could be potentially and partially solved in the framework of fuzzy sets, are presented.
References
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Journal ArticleDOI
Emergence of Scaling in Random Networks
TL;DR: A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
Book
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
TL;DR: In this paper, the authors describe the important ideas in these areas in a common conceptual framework, and the emphasis is on concepts rather than mathematics, with a liberal use of color graphics.
Journal ArticleDOI
Community structure in social and biological networks
Michelle Girvan,Mark Newman +1 more
TL;DR: This article proposes a method for detecting communities, built around the idea of using centrality indices to find community boundaries, and tests it on computer-generated and real-world graphs whose community structure is already known and finds that the method detects this known structure with high sensitivity and reliability.
Journal ArticleDOI
Finding and evaluating community structure in networks.
TL;DR: It is demonstrated that the algorithms proposed are highly effective at discovering community structure in both computer-generated and real-world network data, and can be used to shed light on the sometimes dauntingly complex structure of networked systems.
Journal ArticleDOI
Community detection in graphs
TL;DR: A thorough exposition of community structure, or clustering, is attempted, from the definition of the main elements of the problem, to the presentation of most methods developed, with a special focus on techniques designed by statistical physicists.