DocumentCode :
2849033
Title :
Cohesive subgroup model for graph-based text mining
Author :
Balasundaram, Balabhaskar
Author_Institution :
Sch. of Ind. Eng. & Manage., Oklahoma State Univ., Stillwater, OK
fYear :
2008
fDate :
23-26 Aug. 2008
Firstpage :
989
Lastpage :
994
Abstract :
A k-plex is a graph theoretic generalization of a clique, introduced in social network analysis (SNA) to model tightly knit social subgroups referred to as cohesive subgroups. Clique model was the earliest mathematical model for a cohesive subgroup, but its overly restrictive definition motivated several relaxations including the k-plex model. The models from SNA are suitable, and potentially more realistic cluster models for graph-based clustering and data mining. This article will discuss the applicability of the k-plex model and its advantages compared to the clique model. Some recent developments in integer programming based approaches to identify large k-plexes would be described and the approaches demonstrated on a text mining network.
Keywords :
data mining; graph theory; integer programming; clique model; cluster models; cohesive subgroup model; data mining; graph theoretic generalization; graph-based clustering; graph-based text mining; integer programming; k-plex model; social network analysis; Automation; Biological system modeling; Bridges; Data mining; Internet; Mathematical model; Proteins; Robustness; Social network services; Text mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation Science and Engineering, 2008. CASE 2008. IEEE International Conference on
Conference_Location :
Arlington, VA
Print_ISBN :
978-1-4244-2022-3
Electronic_ISBN :
978-1-4244-2023-0
Type :
conf
DOI :
10.1109/COASE.2008.4626551
Filename :
4626551
Link To Document :
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