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» Using multiple ontologies in information extraction
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KDD
2012
ACM
201views Data Mining» more  KDD 2012»
13 years 2 days ago
Learning from crowds in the presence of schools of thought
Crowdsourcing has recently become popular among machine learning researchers and social scientists as an effective way to collect large-scale experimental data from distributed w...
Yuandong Tian, Jun Zhu
81
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ASPLOS
2008
ACM
14 years 11 months ago
Feedback-driven threading: power-efficient and high-performance execution of multi-threaded workloads on CMPs
Extracting high-performance from the emerging Chip Multiprocessors (CMPs) requires that the application be divided into multiple threads. Each thread executes on a separate core t...
M. Aater Suleman, Moinuddin K. Qureshi, Yale N. Pa...
BMCBI
2008
135views more  BMCBI 2008»
14 years 9 months ago
Inferring the role of transcription factors in regulatory networks
Background: Expression profiles obtained from multiple perturbation experiments are increasingly used to reconstruct transcriptional regulatory networks, from well studied, simple...
Philippe Veber, Carito Guziolowski, Michel Le Borg...
KDD
2008
ACM
138views Data Mining» more  KDD 2008»
15 years 10 months ago
A visual-analytic toolkit for dynamic interaction graphs
In this article we describe a visual-analytic tool for the interrogation of evolving interaction network data such as those found in social, bibliometric, WWW and biological appli...
Xintian Yang, Sitaram Asur, Srinivasan Parthasarat...
WWW
2010
ACM
15 years 4 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...