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ICML
2007
IEEE
16 years 2 months ago
Graph clustering with network structure indices
Graph clustering has become ubiquitous in the study of relational data sets. We examine two simple algorithms: a new graphical adaptation of the k-medoids algorithm and the Girvan...
Matthew J. Rattigan, Marc Maier, David Jensen
ICDM
2009
IEEE
117views Data Mining» more  ICDM 2009»
15 years 8 months ago
Clustering with Multiple Graphs
—In graph-based learning models, entities are often represented as vertices in an undirected graph with weighted edges describing the relationships between entities. In many real...
Wei Tang, Zhengdong Lu, Inderjit S. Dhillon
108
Voted
ICDM
2003
IEEE
119views Data Mining» more  ICDM 2003»
15 years 7 months ago
A Dynamic Adaptive Self-Organising Hybrid Model for Text Clustering
Clustering by document concepts is a powerful way of retrieving information from a large number of documents. This task in general does not make any assumption on the data distrib...
Chihli Hung, Stefan Wermter
CSCLP
2006
Springer
15 years 5 months ago
Efficient Recognition of Acyclic Clustered Constraint Satisfaction Problems
Abstract. In this paper we present a novel approach to solving Constraint Satisfaction Problems whose constraint graphs are highly clustered and the graph of clusters is close to b...
Igor Razgon, Barry O'Sullivan
ICCV
2009
IEEE
6637views Computer Vision» more  ICCV 2009»
16 years 6 months ago
A Markov Clustering Topic Model for Mining Behaviour in Video
This paper addresses the problem of fully automated mining of public space video data. A novel Markov Clustering Topic Model (MCTM) is introduced which builds on existing Dynami...
Timothy Hospedales, Shaogang Gong, Tao Xiang