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» Learning from Logged Implicit Exploration Data
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102
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WWW
2010
ACM
15 years 7 months ago
Large-scale bot detection for search engines
In this paper, we propose a semi-supervised learning approach for classifying program (bot) generated web search traffic from that of genuine human users. The work is motivated by...
Hongwen Kang, Kuansan Wang, David Soukal, Fritz Be...
ICTAI
2002
IEEE
15 years 5 months ago
Data Mining for Selective Visualization of Large Spatial Datasets
Data mining is the process of extracting implicit, valuable, and interesting information from large sets of data. Visualization is the process of visually exploring data for patte...
Shashi Shekhar, Chang-Tien Lu, Pusheng Zhang, Ruli...
119
Voted
TSE
1998
129views more  TSE 1998»
15 years 8 days ago
Inferring Declarative Requirements Specifications from Operational Scenarios
—Scenarios are increasingly recognized as an effective means for eliciting, validating, and documenting software requirements. This paper concentrates on the use of scenarios for...
Axel van Lamsweerde, Laurent Willemet
100
Voted
ICPP
2007
IEEE
15 years 7 months ago
A Meta-Learning Failure Predictor for Blue Gene/L Systems
The demand for more computational power in science and engineering has spurred the design and deployment of ever-growing cluster systems. Even though the individual components use...
Prashasta Gujrati, Yawei Li, Zhiling Lan, Rajeev T...
ICML
2004
IEEE
15 years 6 months ago
Learning a kernel matrix for nonlinear dimensionality reduction
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul