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» Clustering Improves the Exploration of Graph Mining Results
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WSDM
2009
ACM
115views Data Mining» more  WSDM 2009»
15 years 6 months ago
Discovering and using groups to improve personalized search
Personalized Web search takes advantage of information about an individual to identify the most relevant results for that person. A challenge for personalization lies in collectin...
Jaime Teevan, Meredith Ringel Morris, Steve Bush
VLDB
1997
ACM
169views Database» more  VLDB 1997»
15 years 4 months ago
Mining Insurance Data at Swiss Life
Huge masses of digital data about products, customers and competitors have become available for companies in the services sector. In order to exploit its inherent (and often hidde...
Jörg-Uwe Kietz, Ulrich Reimer, Martin Staudt
BMCBI
2008
226views more  BMCBI 2008»
14 years 12 months ago
ProteoLens: a visual analytic tool for multi-scale database-driven biological network data mining
Background: New systems biology studies require researchers to understand how interplay among myriads of biomolecular entities is orchestrated in order to achieve high-level cellu...
Tianxiao Huan, Andrey Y. Sivachenko, Scott H. Harr...
AUSDM
2008
Springer
230views Data Mining» more  AUSDM 2008»
15 years 1 months ago
Combining Structure and Content Similarities for XML Document Clustering
This paper proposes a clustering approach that explores both the content and the structure of XML documents for determining similarity among them. Assuming that the content and th...
Tien Tran, Richi Nayak, Peter Bruza
PAMI
2007
196views more  PAMI 2007»
14 years 11 months ago
Clustering and Embedding Using Commute Times
This paper exploits the properties of the commute time between nodes of a graph for the purposes of clustering and embedding, and explores its applications to image segmentation a...
Huaijun Qiu, Edwin R. Hancock