Mining for Reengineering: An Application to Semantic Wikis Using Formal and Relational Concept Analysis
Identifieur interne : 000031 ( Main/Curation ); précédent : 000030; suivant : 000032Mining for Reengineering: An Application to Semantic Wikis Using Formal and Relational Concept Analysis
Auteurs : Lian Shi [France] ; Yannick Toussaint [France] ; Amedeo Napoli [France] ; Alexandre Blansché [France]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2011.
Abstract
Abstract: 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.
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DOI: 10.1007/978-3-642-21064-8_29
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Concept Analysis</title><author><name sortKey="Shi, Lian" sort="Shi, Lian" uniqKey="Shi L" first="Lian" last="Shi">Lian Shi</name><affiliation><mods:affiliation>LORIA CNRS – INRIA Nancy Grand-Est – Nancy Université, équipe Orpailleur, BP 70239, F-54506, Vandœuvre-lès-Nancy</mods:affiliation></affiliation><affiliation wicri:level="1"><mods:affiliation>E-mail: Lian.Shi@loria.fr</mods:affiliation><country wicri:rule="url">France</country></affiliation></author><author><name sortKey="Toussaint, Yannick" sort="Toussaint, Yannick" uniqKey="Toussaint Y" first="Yannick" last="Toussaint">Yannick Toussaint</name><affiliation><mods:affiliation>LORIA CNRS – INRIA Nancy Grand-Est – Nancy Université, équipe Orpailleur, BP 70239, F-54506, Vandœuvre-lès-Nancy</mods:affiliation></affiliation><affiliation wicri:level="1"><mods:affiliation>E-mail: Yannick.Toussaint@loria.fr</mods:affiliation><country wicri:rule="url">France</country></affiliation></author><author><name sortKey="Napoli, Amedeo" sort="Napoli, Amedeo" uniqKey="Napoli A" first="Amedeo" last="Napoli">Amedeo Napoli</name><affiliation><mods:affiliation>LORIA CNRS – INRIA Nancy Grand-Est – Nancy Université, équipe Orpailleur, BP 70239, F-54506, Vandœuvre-lès-Nancy</mods:affiliation></affiliation><affiliation wicri:level="1"><mods:affiliation>E-mail: Amedeo.Napoli@loria.fr</mods:affiliation><country wicri:rule="url">France</country></affiliation></author><author><name sortKey="Blansche, Alexandre" sort="Blansche, Alexandre" uniqKey="Blansche A" first="Alexandre" last="Blansché">Alexandre Blansché</name><affiliation><mods:affiliation>Laboratoire LITA, Université Paul Verlaine, Île du Saulcy, F-57000, Metz</mods:affiliation></affiliation><affiliation wicri:level="1"><mods:affiliation>E-mail: alexandre.blansche@univ-metz.fr</mods:affiliation><country wicri:rule="url">France</country></affiliation></author></analytic><monogr></monogr><series><title level="s">Lecture Notes in Computer Science</title><imprint><date>2011</date></imprint><idno type="ISSN">0302-9743</idno><idno type="eISSN">1611-3349</idno><idno type="ISSN">0302-9743</idno></series><idno type="istex">31F2380466DC6CD3DA569A593F9714449C1F1D30</idno><idno type="DOI">10.1007/978-3-642-21064-8_29</idno><idno type="ChapterID">29</idno><idno type="ChapterID">Chap29</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0302-9743</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: 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. 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