A Mutually Beneficial Integration of Data Mining and Information Extraction

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 announcement postings from an Internet newsgroup.

• Type: Conference
• Year: 2000
• Where: AAAI
• Authors: Un Yong Nahm, Raymond J. Mooney
• Keywords: AAAI 2000, Data Mining, Intelligent Agents, Text Mining, Unstructured Text