Concept Lattices and Their Applications: Fourth by Jon Ducrou, Peter Eklund, Tim Wilson (auth.), Sadok Ben

By Jon Ducrou, Peter Eklund, Tim Wilson (auth.), Sadok Ben Yahia, Engelbert Mephu Nguifo, Radim Belohlavek (eds.)

This ebook constitutes the refereed complaints of the Fourth overseas convention on idea Lattices and their functions, CLA 2006, held in Tunis, Tunisia, October 30-November 1, 2006.

The 18 revised complete papers including three invited contributions provided have been rigorously reviewed and chosen from forty-one submissions. the themes comprise formal idea research, foundations of FCA, mathematical constructions relating to FCA, dating of FCA to different equipment of information research, visualization of information in FCA, and purposes of FCA.

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Additional resources for Concept Lattices and Their Applications: Fourth International Conference, CLA 2006 Tunis, Tunisia, October 30-November 1, 2006 Selected Papers

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Moreover, the system has to provide channels for allowing communications with human agents, such as experts and end-users. The resulting kddk system architecture has to be reusable in any application domain. Accordingly, the integration of such a kddk system in the framework of the semantic Web can be seen as follows. e. databases, sets of documents, are explored, navigated, and queried, under the supervision of an analyst, thanks to a kddk process guided by knowledge bases of the domain. The data are prepared and manipulated by the kddk process, while the knowledge units are validated by the analyst, and then manipulated by the inference engine.

Ben Yahia et al. ): CLA 2006, LNAI 4923, pp. 22–41, 2008. c Springer-Verlag Berlin Heidelberg 2008 First Elements on Knowledge Discovery Guided by Domain Knowledge 23 Rough Data, databases ↓ Domain understanding ↓ Data selection (windowing) Selected data ↓ Cleaning / Preparation Prepared data ↓ Data mining process (discovering patterns) ↓ Numerical and symbolic KDD methods Discovered patterns ↓ Post-processing of discovered patterns ↓ Interpretation / Evaluation Knowledge units for knowledge systems and problem-solving Fig.

The idea is then to make suggestions for protocol evolutions based on frequently performed adaptations. In knowledge-intensive cbr, the reuse of cases is generally based on adaptation, the goal of which is to solve the target problem by adapting the solution of a source case. The adaptation process is based on adaptation knowledge that –for the main part– is domain-dependent, and thus needs to be acquired for a new application of cbr. g. in knowledge-intensive case-based reasoning systems [1]. In parallel, the Semantic Web technology relies on the availability of large amount of knowledge in various forms [16,41].

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