Sugato Basu, Raymond J. Mooney, Krupakar V. Pasupuleti, and Joydeep Ghosh. Evaluating the novelty of text-mined rules using lexical knowledge. In Knowledge Discovery and Data Mining, pages 233--238, 2001. Home/Search Document Details and Download
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Text Mining with Information Extraction - Nahm, Mooney (2002) (2 citations) Self-citation (Mooney) (Correct)
....metrics for evaluating the interestingness of text mined rules are clearly needed. One idea is to use a hierarchical network to measure the semantic distance between the words in a rule, preferring surprising rules where this distance is larger. Such an algorithm using WordNet has been proposed (Basu et al. 2001); however, WordNet is too general and huge a hierarchy to be useful in every speci c domain. Using a smaller domain speci c taxonomy would be helpful for nding more interesting rules. For example, this would allow ranking the rule beer diapers above beer pretzels since beer and pretzels ....
Basu, S.; Mooney, R. J.; Pasupuleti, K. V.; and Ghosh, J. 2001. Evaluating the novelty of text-mined rules using lexical knowledge. In Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 233-239.
Augmented Trading: From news articles to stock price.. - van Bunningen (2004) (Correct)
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Sugato Basu, Raymond J. Mooney, Krupakar V. Pasupuleti, and Joydeep Ghosh. Evaluating the novelty of text-mined rules using lexical knowledge. In Knowledge Discovery and Data Mining, pages 233--238, 2001.
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