By Rainer Schmidt, Heike Weiss, Georg Fuellen (auth.), Petra Perner (eds.)
This booklet constitutes the refereed complaints of the twelfth business convention on information Mining, ICDM 2012, held in Berlin, Germany in July 2012. The 22 revised complete papers provided have been rigorously reviewed and chosen from ninety seven submissions. The papers are equipped in topical sections on information mining in medication and biology; information mining for power undefined; information mining in site visitors and logistic; information mining in telecommunication; information mining in engineering; idea in facts mining; concept in info mining: clustering; idea in facts mining: organization rule mining and choice rule mining.
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Extra info for Advances in Data Mining. Applications and Theoretical Aspects: 12th Industrial Conference, ICDM 2012, Berlin, Germany, July 13-20, 2012. Proceedings
University of Helsinki (2002) 8. : Subgroup discovery with CN2-SD. Journal of Machine Learning Research 5, 153–188 (2004) 9. : Data Preparation for Data Mining. Morgan Kaufmann (1999) 10. 5. IEEE Transactions on Knowledge and Data Engineering 14, 438–444 (2002) 11. : Introduction to Data Mining. Pearson Education (2006) 12. int/en/ SOHAC: Eﬃcient Storage of Tick Data That Supports Search and Analysis Gabor I. hu Abstract. 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.
LNCS (LNAI), vol. 5239, pp. 18–43. Springer, Heidelberg (2008) 15. : Case-Based Reasoning Systems in the Health Sciences: A Survey of Recent Trends and Developments. IEEE Transactions on Systems, Man, and Cybernetics 41(4), 421–434 (2011) 16. : Medical subject headings (mesh). Bulletin of the Medical Library Association 88(3), 265–266 (2000) 17. : Concept learning and heuristic classification in weak-theory domains. Artificial Intelligence 45(1-2), 229–263 (1990) 18. : Reasoning about evidence in causal explanations.
Hybrid systems were not identified either as a major theme in the CBR conference literature, hence the non-existence of machine learning / data mining combination (#4) for example. Research Themes in the Case-Based Reasoning in Health Sciences Core Literature 21 We would also like to comment on the highly cited papers in CBR-HS, namely papers #1 (PROTOS , 290 citations), #2 (CASEY , 239 citations), #3 (PROTOS , 156 citations), and #6 (SHRINK , 81 citations). These papers clearly demonstrate that CBR-HS papers can have an impact as high and even higher as those in the CBR conference literature, where the top ranked papers receive 137, 117, 92, and 82 citations on Google Scholar.