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SIGIR
2006
ACM
14 years 1 months ago
Large scale semi-supervised linear SVMs
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Vikas Sindhwani, S. Sathiya Keerthi
ATC
2006
Springer
13 years 11 months ago
Ubisafe Computing: Vision and Challenges (I)
In recent years, a variety of new computing paradigms have been proposed for various purposes. It is true that many of them intend to and really can gratify some of the people some...
Jianhua Ma, Qiangfu Zhao, Vipin Chaudhary, Jingde ...
FLAIRS
2000
13 years 9 months ago
Domain-Specific Knowledge Acquisition and Classification Using WordNet
For manyknowledgeintensive applications, it is necessary to have extensive domain-specific knowledgein addition to general-purpose knowledge bases usually built around MachineRead...
Dan I. Moldovan, Roxana Girju
CHI
2011
ACM
12 years 11 months ago
Apolo: making sense of large network data by combining rich user interaction and machine learning
Extracting useful knowledge from large network datasets has become a fundamental challenge in many domains, from scientific literature to social networks and the web. We introduc...
Duen Horng Chau, Aniket Kittur, Jason I. Hong, Chr...
CIKM
2011
Springer
12 years 7 months ago
Exploiting longer cycles for link prediction in signed networks
We consider the problem of link prediction in signed networks. Such networks arise on the web in a variety of ways when users can implicitly or explicitly tag their relationship w...
Kai-Yang Chiang, Nagarajan Natarajan, Ambuj Tewari...