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ICDM
2010
IEEE
230views Data Mining» more  ICDM 2010»
15 years 1 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
WSDM
2010
ACM
315views Data Mining» more  WSDM 2010»
16 years 1 months ago
SBotMiner: Large Scale Search Bot Detection
In this paper, we study search bot traffic from search engine query logs at a large scale. Although bots that generate search traffic aggressively can be easily detected, a large ...
Fang Yu, Yinglian Xie, Qifa Ke
125
Voted
AAAI
1998
15 years 5 months ago
An Architecture for Exploring Large Design Spaces
We describe an architecture for exploring very large design spaces, for example, spaces that arise when design candidates are generated by combining components systematically from...
John R. Josephson, B. Chandrasekaran, Mark Carroll...
BMCBI
2010
175views more  BMCBI 2010»
15 years 3 months ago
Calibur: a tool for clustering large numbers of protein decoys
Background: Ab initio protein structure prediction methods generate numerous structural candidates, which are referred to as decoys. The decoy with the most number of neighbors of...
Shuai Cheng Li, Yen Kaow Ng
ICDE
2009
IEEE
290views Database» more  ICDE 2009»
16 years 5 months ago
GraphSig: A Scalable Approach to Mining Significant Subgraphs in Large Graph Databases
Graphs are being increasingly used to model a wide range of scientific data. Such widespread usage of graphs has generated considerable interest in mining patterns from graph datab...
Sayan Ranu, Ambuj K. Singh