Text mining concerns applying data mining techniques to unstructured text. Information extraction (IE) is a form of shallow text understanding that locates specific pieces of data in natural language documents, transforming unstructured text into a structured database. This paper describes a system called DiscoTEX, that combines IE and data mining methodologies to perform text mining as well as improve the performance of the underlying extraction system. Rules mined from a database extracted from a corpus of texts are used to predict additional information to extract from future documents, thereby improving the recall of IE. Encouraging results are presented on applying these techniques to a corpus of computer job postings from an Internet newsgroup.

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In Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI-00), pp. 627-632, Austin, TX, July 2000.

@InProceedings{nahm:aaai00, title={A Mutually Beneficial Integration of Data Mining and Information Extraction}, author={Un Yong Nahm and Raymond J. Mooney}, booktitle={Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI-00)}, month={July}, address={Austin, TX}, key={DiscoTEX, KDD, IE}, pages={627-632}, url="http://www.cs.utexas.edu/users/ai-lab?nahm:aaai00", year={2000} }