Download e-book for iPad: Advances in Data Mining. Applications and Theoretical by Rainer Schmidt, Heike Weiss, Georg Fuellen (auth.), Petra

By Rainer Schmidt, Heike Weiss, Georg Fuellen (auth.), Petra Perner (eds.)

ISBN-10: 3642314872

ISBN-13: 9783642314872

ISBN-10: 3642314880

ISBN-13: 9783642314889

This ebook constitutes the refereed complaints of the twelfth business convention on facts Mining, ICDM 2012, held in Berlin, Germany in July 2012. The 22 revised complete papers offered have been conscientiously reviewed and chosen from ninety seven submissions. The papers are equipped in topical sections on info mining in medication and biology; information mining for strength undefined; info mining in site visitors and logistic; information mining in telecommunication; info mining in engineering; conception in information mining; conception in facts mining: clustering; idea in facts mining: organization rule mining and choice rule mining.

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Artificial Intelligence 45(1-2), 229–263 (1990) 18. : Reasoning about evidence in causal explanations. In: Proceedings of AAAI 1988. Seventh National Conference on Artificial Intelligence, pp. 21–26 (1988) 19. : Protos: an exemplar-based learning apprentice. In: Proceedings of the Fourth International Workshop on Machine Learning, pp. 12–23. Morgan Kaufmann, Los Altos (1987) 20. : Case-Based Reasoning in CARE-PARTNER: Gathering Evidence for Evidence-Based Medical Practice. , Cunningham, P. ) EWCBR 1998.

This study has identified interesting and major research themes and trends characteristic of applied domains such as health sciences domains. I has also compared these themes with those in the CBR conference literature, and found both common elements and differences. This analysis of CBR-HS literature also permits to identify potential future research directions. Future directions include visualization and evolution tracking of CBR-HS literature, comparison with automatic classification, as well automatizing the indexing system as much as feasible.

Storage of tick data is a challenging problem because two criteria have to be fulfilled simultaneously: the storage structure should allow fast execution of queries and the data should not occupy too much space on the hard disk or in the main memory. In this paper, we present a clustering-based solution, and we introduce a new clustering algorithm that is designed to support the storage of tick data. We evaluate our algorithm both on publicly available real-world datasets, as well as real-world tick data from the financial domain provided by one of the world-wide most renowned investment bank.

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Advances in Data Mining. Applications and Theoretical Aspects: 12th Industrial Conference, ICDM 2012, Berlin, Germany, July 13-20, 2012. Proceedings by Rainer Schmidt, Heike Weiss, Georg Fuellen (auth.), Petra Perner (eds.)


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