Advanced Data Mining and Applications: 7th International by Yong-Bin Kang, Shonali Krishnaswamy (auth.), Jie Tang, Irwin

By Yong-Bin Kang, Shonali Krishnaswamy (auth.), Jie Tang, Irwin King, Ling Chen, Jianyong Wang (eds.)

The two-volume set LNAI 7120 and LNAI 7121 constitutes the refereed complaints of the seventh overseas convention on complex information Mining and functions, ADMA 2011, held in Beijing, China, in December 2011. The 35 revised complete papers and 29 brief papers awarded including three keynote speeches have been rigorously reviewed and chosen from 191 submissions. The papers hide a variety of subject matters featuring unique examine findings in information mining, spanning functions, algorithms, software program and platforms, and utilized disciplines.

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Extra resources for Advanced Data Mining and Applications: 7th International Conference, ADMA 2011, Beijing, China, December 17-19, 2011, Proceedings, Part I

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Theoretical Computer Science 250(1-2), 1–30 (2001) 19. : Self-organising maps. Information Sciences (1995) 20. : Some methods for classification and analysis of multivariate observations. In: Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, vol. 1 (1967) 21. : The EM algorithm and extensions. Wiley Series in Probability and Statistics, 2nd edn. Wiley (2008) 22. : Disaggregation of bipolar-valued outranking relations. D. ) MCO. CCIS, vol. 14, pp. 204–213. Springer, Heidelberg (2008) 23.

Finally, Section 6 concludes this paper. 1 Preliminaries Frequent Itemsets Given a set of distinct items Γ = {i1 , i2 , · · · , in } where |Γ | = n denotes the size of Γ , a subset X ⊆ Γ is called an itemset; suppose |X| = k, we call X a k-itemset. A concise expression of itemset X = {x1 , x2 , · · · , xm } is x1 x2 · · · xm . A database D = {T1 , T2 , · · · , Tv } is a collection wherein each transaction is a subset of Γ , namely an itemset. , the id of Ti is i. The absolute support (AS ) of an itemset α, also called the weight of α , is the number of transactions which cover α, denoted Λ(α, D(v)), Λ(α) in short, is {|T ||T ∈ D ∧ α ⊆ T }; the relative support (RS ) of an itemset α is the ratio of AS with respect to |D|, denoted Λr (α) = Λ(α) v .

Nature 435(7043), 814–818 (2005) 27. : Wavecluster: A multi-resolution clustering approach for very large spatial databases. In: Proceedings of 24rd International Conference on Very Large Data Bases VLDB 1998, pp. 428–439. Morgan Kaufmann (1998) 28. : Metaheuristics - From Design to Implementation. Wiley (2009) 29. : BIRCH: an efficient data clustering method for very large databases. In: SIGMOD 1996: Proceedings of the 1996 ACM SIGMOD International Conference on Management of Data, pp. 103–114. ACM Press (1996) 30.

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