Rating the interest of rules induced from data and within texts

Presents an application based on an evaluation of the interestingness of the rules induced from examples using inductive text mining (ITM). The better-known deductive text mining is called information extraction, and amounts to finding instances of a predefined pattern in a set of texts. ITM looks for unknown patterns or rules to discover inside a set of texts. We mainly discuss two of the problems of ITM: building ontologies of concepts, and extracting patterns.