Extraction of purpose data using surface text patterns

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 and patterns were extracted from the returned documents by automated means and standardized. The precision of each pattern and the average precision for each group were computed. The extracted patterns were then used to extract purpose data. The results for extraction from the web have been reported.