Titlebook: Advances in Data Mining; Applications in Medi Petra Perner Conference proceedings 2006 Springer-Verlag Berlin Heidelberg 2006 Alignment.Fuz

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Philip R. Heath,Klaus Heiner Kampsovery from medical literature. This research builds on previous work on concept mining from medical literature for indexing purposes and proposes to learn semantic relationships names between concepts learnt. Previous ConceptMiner system did learn pairs of concepts, expressing a relationship between

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Topological functors from factorization,t the main stress is focussed on the experimental studies, the aim of which was to examine its usefulness in knowledge discovery and rule extraction for classification task of medical data. The tests were made using the well-known benchmark data sets from UCI, as well as two other data sets collecte

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Disconnectednesses: Two Examples, spam problem domain. Several experiments with different feature selection methods and content-based filtering techniques are carried out and discussed. Information Gain, ..-text, Mutual Information and Document Frequency feature selection methods have been analysed in conjunction with Naïve Bayes,

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Categories and Commutative Algebrah the raw data that can be gained from a web log file in order to facilitate a later use in different analyses. Further, we look at the question which requirements a good web log analysis software needs to meet and offer an overview over current and future analysis practices including their advantag

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Categories and Commutative Algebraics and unstructured contents. In this paper we present a web browsing support system that proposes personalized contents. It is integrated in the content management system and it runs on the server hosting the site. It processes periodically site contents, extracting vectors of the most significant

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