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» Learning from Multiple Sources of Inaccurate Data
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WWW
2010
ACM
15 years 10 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...
146
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ICDE
2010
IEEE
290views Database» more  ICDE 2010»
15 years 7 months ago
The Model-Summary Problem and a Solution for Trees
Modern science is collecting massive amounts of data from sensors, instruments, and through computer simulation. It is widely believed that analysis of this data will hold the key ...
Biswanath Panda, Mirek Riedewald, Daniel Fink
AAAI
2006
15 years 4 months ago
Automatically Labeling the Inputs and Outputs of Web Services
Information integration systems combine data from multiple heterogeneous Web services to answer complex user queries, provided a user has semantically modeled the service first. T...
Kristina Lerman, Anon Plangprasopchok, Craig A. Kn...
JASIS
2007
121views more  JASIS 2007»
15 years 3 months ago
Can citation analysis of Web publications better detect research fronts?
We present evidence that, in some research fields, research published in journals and reported on the Web may collectively represent different evolutionary stages of the field wit...
Dangzhi Zhao, Andreas Strotmann
TIP
2010
154views more  TIP 2010»
15 years 1 months ago
Projective Nonnegative Graph Embedding
—We present in this paper a general formulation for nonnegative data factorization, called projective nonnegative graph embedding (PNGE), which 1) explicitly decomposes the data ...
Xiaobai Liu, Shuicheng Yan, Hai Jin