Title
The Recognition of Multiple Virtual Identities Association Based on Multi-agent System.
Abstract
The recognition of multiple virtual identities association has aroused extensive attention, which can be widely used in author identification, forum spammer detection and other fields. We focus on the features of authors behavior on the dynamic data. This paper applies multi-agent system to the authors information mining fields and proposes a recognition model based on multi-agent system: MVIA-MAS. We cluster the author information in each time slice in parallel and then use association rule mining to find the target author groups, in which the multiple virtual identities are considered associated. Experiments show that the model has a better overall performance.
Year
DOI
Venue
2013
10.1007/978-3-642-55192-5_4
AGENTS AND DATA MINING INTERACTION (ADMI 2013)
Keywords
Field
DocType
Multiple virtual identities,Multi-agent system,Time slice
Data mining,Preemption,Computer science,Information mining,Multi-agent system,Dynamic data,Association rule learning,Artificial intelligence,Machine learning,Spamming
Conference
Volume
ISSN
Citations 
8316
0302-9743
0
PageRank 
References 
Authors
0.34
11
5
Name
Order
Citations
PageRank
Le Li121.72
Weidong Xiao231459.09
Changhua Dai300.34
Junyi Xu4248.39
Bin Ge500.34