Learning with Markov logic networks : transfer learning, structure learning, and an application to Web query disambiguation
Traditionally, machine learning algorithms assume that training data is provided as a set of independent instances, each of which can be described as a feature vector. In contrast, many domains of interest are inherently multi-relational, consisting of entities connected by a rich set of relations....
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| Format: | Others |
| Language: | English |
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2011
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| Online Access: | http://hdl.handle.net/2152/10574 |