This paper describes the extraction from Wikipedia of lexical reference rules, identifying references to term meanings triggered by other terms. We present extraction methods geared to cover the broad range of the lexical reference relation and analyze them extensively. Most extraction methods yield high precision levels, and our rule-base is shown to perform better than other automatically con...

The rule ontology is a generalized, condensed, and specifically rearranged version of the existing rules. Rule acquisition research is relatively unpopular while there are many works on ontology learning. We proposed an automatic rule acquisition procedure using ontology, named Rule To Onto, that includes information about the rule components and their structures. We started from the idea that ...

Artificial neural networks (ANNs) are essentially a ‘black box’ technology. The lack of an explanation component prevents the full and complete exploitation of this form of machine learning. This chapter presents an historical perspective on rule extraction from artificial neural networks beginning with 6 ways in which the ANN paradigm may be enriched through the addition of rule extraction / e...