2011 | OriginalPaper | Buchkapitel
Mining for Reengineering: An Application to Semantic Wikis Using Formal and Relational Concept Analysis
verfasst von : Lian Shi, Yannick Toussaint, Amedeo Napoli, Alexandre Blansché
Erschienen in: The Semanic Web: Research and Applications
Verlag: Springer Berlin Heidelberg
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Semantic wikis enable collaboration between human agents for creating knowledge systems. In this way, data embedded in semantic wikis can be mined and the resulting knowledge patterns can be reused to extend and improve the structure of wikis. This paper proposes a method for guiding the reengineering and improving the structure of a semantic wiki. This method suggests the creation of categories and relations between categories using Formal Concept Analysis (FCA) and Relational Concept Analysis (RCA). FCA allows the design of a concept lattice while RCA provides relational attributes completing the content of formal concepts. The originality of the approach is to consider the wiki content from FCA and RCA points of view and to extract knowledge units from this content allowing a factorization and a reengineering of the wiki structure. This method is general and does not depend on any domain and can be generalized to every kind of semantic wiki. Examples are studied throughout the paper and experiments show the substantial results.