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This paper presents the concept of surface text patterns for extracting purpose data from the web. In order to obtain an optimal set of patterns, we have developed a method for learning purpose patterns automatically. A corpus was downloaded from the Internet using bootstrapping by providing a few hand-crafted examples of each purpose pattern to a generic search engine. This corpus was then tagged...
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...
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