A Mutually Beneficial Integration of Data Mining and Information Extraction (2000)
| Venue: | In Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI-2000 |
| Citations: | 45 - 6 self |
BibTeX
@INPROCEEDINGS{Nahm00amutually,
author = {Un Yong Nahm and Raymond J. Mooney},
title = {A Mutually Beneficial Integration of Data Mining and Information Extraction},
booktitle = {In Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI-2000},
year = {2000},
pages = {627--632}
}
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Abstract
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.
