document: Evaluating the novelty of text-mined rules using lexical knowledge In this paper , we present a new method of estimating the novelty of rules discovered by data-mining methods using WordNet , a lexical knowledge-base of English words . We assess the novelty of a rule by the average semantic distance in a knowledge hierarchy between the words in the antecedent and the consequent of the rule - the more the average distance , more is the novelty of the rule . The novelty of rules extracted by the DiscoTEX text-mining system on Amazon.com book descriptions were evaluated by both human subjects and by our algorithm . By computing correlation coefficients between pairs of human ratings and between human and automatic ratings , we found that the automatic scoring of rules based on our novelty measure correlates with human judgments about as well as human judgments correlate with one another . @Text mining
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