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Extracting instances of a given target relation from a given Web page corpus seems to be the basic work to exploit nearly endless source of knowledge which provided by the World Wide Web. Supervised learning requires a large amount of labeled data, but the data labeling process can be expensive and time consuming. In this paper we present a kernel-based weakly supervised machine learning algorithm...
Extracting instances of a given target relation from a given Web page corpus seems to be the basic work to exploit nearly endless source of knowledge which provided by the World Wide Web. In this paper, we present an automated system which could extract instances of an arbitrary given binary relation from Chinese Web documents in domain of football games. Different syntactic sources are combined by...
The dependency structure language model was proposed to overcome the limitation of unigram and bigram models in topic detection and tracking (TDT). But its structure is based on mathematical models, which may has problems to express information. In this paper a new approach of topic tracking of Chinese news articles is presented which improves the existing ones with temporal information. The technique...
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