Abstract
Many data mining techniques are these days in use for ontology learning – text mining, Web mining, graph mining, link analysis,
relational data mining, and so on. In the current state-of-the-art bundle there is a lack of “software mining” techniques.This term denotes the process of extracting knowledge out of source code. In this paper we approach the software mining taskwith a combination of text mining and link analysis techniques. We discuss how each instance (i.e. a programming constructsuch as a class or a method) can be converted into a feature vector that combines the information about how the instance isinterlinked with other instances, and the information about its (textual) content. The so-obtained feature vectors serve asthe basis for the construction of the domain ontology with OntoGen, an existing system for semi-automatic data-driven ontologyconstruction.
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