Data Mining and Knowledge Discovery Handbook (Springer by Oded Maimon, Lior Rokach

By Oded Maimon, Lior Rokach

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This ebook organizes key ideas, theories, criteria, methodologies, developments, demanding situations and purposes of knowledge mining and data discovery in databases. It first surveys, then offers accomplished but concise algorithmic descriptions of tools, together with vintage tools plus the extensions and novel tools constructed lately. It additionally provides in-depth descriptions of information mining purposes in a variety of interdisciplinary industries.
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Ak ). Each attribute ai in a particular record r j has a value φ (r j , ai ) from a domain D. The value of the attribute may also be empty and is therefore included in D. The following relations (partial orderings) are defined over D, namely less or equal (≤), equal (=) and, greater or equal (≥) all having the standard meaning. Then (a1 , a2 , a3 , . . , am )⇒ (a1 μ 1 a2 μ 2 a3 . . μ m−1 am ), where each μ i ∈ {≤, =, ≥}, is a an ordinal association rule if: 1. am occur together (are non-empty) in at least s% of the n records, where s is the support of the rule; 2.

Di Martion, J. A data cleaning solution by Perl scripts for the KDD Cup 2003 task 2, ACM SIGKDD Explorations Newsletter 2003; 5(2):158-159. , & Motwani, R. Robust and efficient fuzzy match for online data cleaning. Proceedings of ACM SIGMOD International Conference on Management of Data; 2003 june 9-12; San Diego, CA. 313-324. , Vesonder, G. , & Wright, J. R. Data quality through knowledge engineering. C. 705-710. Fayyad, U. , From Data Mining to Knowledge Discovery: An Overview. In Advances in Knowledge Discovery and Data Mining, Fayyad, U.

Rokach, L. and Maimon, O. , Information Retrieval System for Medical Narrative Reports, Lecture Notes in Artificial intelligence 3055, page 217-228 SpringerVerlag, 2004. Rokach, L. and Maimon, O. , Selective voting-getting more for less in sensor fusion, International Journal of Pattern Recognition and Artificial Intelligence 20 (3) (2006), pp. 329–350. Rokach, L. , Theory and applications of attribute decomposition, IEEE International Conference on Data Mining, IEEE Computer Society Press, pp. 473–480, 2001.

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