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» Spectrum based fraud detection in social networks
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KDD
2006
ACM
157views Data Mining» more  KDD 2006»
14 years 8 months ago
Using structure indices for efficient approximation of network properties
Statistics on networks have become vital to the study of relational data drawn from areas such as bibliometrics, fraud detection, bioinformatics, and the Internet. Calculating man...
Matthew J. Rattigan, Marc Maier, David Jensen
WCNC
2010
IEEE
13 years 11 months ago
A Comparison between Stand-Alone and Distributed Architectures for Spectrum Hole Detection
Abstract—In this paper two different cognitive radio architectures, i.e. stand-alone and distributed, are proposed for spectrum sensing purposes. In particular, both architecture...
Luca Bixio, Marina Ottonello, Mirco Raffetto, Carl...
WWW
2011
ACM
13 years 2 months ago
Predicting popular messages in Twitter
Social network services have become a viable source of information for users. In Twitter, information deemed important by the community propagates through retweets. Studying the c...
Liangjie Hong, Ovidiu Dan, Brian D. Davison
ASUNAM
2010
IEEE
13 years 9 months ago
Detecting Highly Overlapping Communities with Model-Based Overlapping Seed Expansion
Abstract--As research into community finding in social networks progresses, there is a need for algorithms capable of detecting overlapping community structure. Many algorithms hav...
Aaron McDaid, Neil Hurley
MOBIHOC
2009
ACM
14 years 8 months ago
Spectrum auction framework for access allocation in cognitive radio networks
Cognitive radio networks are emerging as a promising technology for the efficient use of radio spectrum. In these networks, there are two categories of networks on different chann...
Gaurav S. Kasbekar, Saswati Sarkar