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» Clustering-based approaches to SAGE data mining
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KDD
2006
ACM
198views Data Mining» more  KDD 2006»
14 years 5 months ago
Event detection from evolution of click-through data
Previous efforts on event detection from the web have focused primarily on web content and structure data ignoring the rich collection of web log data. In this paper, we propose t...
Qiankun Zhao, Tie-Yan Liu, Sourav S. Bhowmick, Wei...
DBA
2004
113views Database» more  DBA 2004»
13 years 6 months ago
A Quality Measure for Distributed Clustering
Clustering has become an increasingly important task in modern application domains. Mostly, the data are originally collected at different sites. In order to extract information f...
Eshref Januzaj, Hans-Peter Kriegel, Martin Pfeifle
PKDD
2010
Springer
235views Data Mining» more  PKDD 2010»
13 years 3 months ago
Online Structural Graph Clustering Using Frequent Subgraph Mining
The goal of graph clustering is to partition objects in a graph database into different clusters based on various criteria such as vertex connectivity, neighborhood similarity or t...
Madeleine Seeland, Tobias Girschick, Fabian Buchwa...
KDD
2002
ACM
166views Data Mining» more  KDD 2002»
14 years 5 months ago
Frequent term-based text clustering
Text clustering methods can be used to structure large sets of text or hypertext documents. The well-known methods of text clustering, however, do not really address the special p...
Florian Beil, Martin Ester, Xiaowei Xu
ICDM
2010
IEEE
230views Data Mining» more  ICDM 2010»
13 years 3 months ago
Clustering Large Attributed Graphs: An Efficient Incremental Approach
In recent years, many networks have become available for analysis, including social networks, sensor networks, biological networks, etc. Graph clustering has shown its effectivenes...
Yang Zhou, Hong Cheng, Jeffrey Xu Yu