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

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

ISBN-10: 3642258522

ISBN-13: 9783642258527

ISBN-10: 3642258530

ISBN-13: 9783642258534

The two-volume set LNAI 7120 and LNAI 7121 constitutes the refereed complaints of the seventh foreign convention on complicated facts 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 conscientiously reviewed and chosen from 191 submissions. The papers conceal quite a lot of issues providing unique study findings in info mining, spanning functions, algorithms, software program and platforms, and utilized disciplines.

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Read Online or Download Advanced Data Mining and Applications: 7th International Conference, ADMA 2011, Beijing, China, December 17-19, 2011, Proceedings, Part I PDF

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Additional 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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An Approximate Approach for Mining Recently Frequent Itemsets from Data Streams. , Trujillo, J. ) DaWaK 2006. LNCS, vol. 4081, pp. 352–362. Springer, Heidelberg (2006) 20. : DSTree: A Tree Structure for the Mining of Frequent Sets from Data Streams. In: Proc. ICDM (2006) 21. : Finding Maximal Frequent Itemsets over Online Data Streams Adaptively. In: Proc. ICDM (2005) 22. : Approximate Frequency Counts over Streaming Data. In: Proc. VLDB (2002) 23. : Verifying and Mining Frequent Patterns from Large Windows over Data Streams.

16–25. ACM (2007) 11. : Community detection in graphs. Physics Reports 486(3-5), 75–174 (2010) 12. : UCI machine learning repository (2010) 13. : CURE: an efficient clustering algorithm for large databases. , Franklin, M. ) SIGMOD 1998: Proceedings of the 1998 ACM SIGMOD International Conference on Management of Data, pp. 73–84. ACM Press (1998) 14. : Nouvelles recherches sur la distribution florale. Bulletin de la Societe Vaudoise de Sciences Naturelles 44, 223–370 (1908) 15. : Algorithms for clustering data.

4081, pp. 352–362. Springer, Heidelberg (2006) 20. : DSTree: A Tree Structure for the Mining of Frequent Sets from Data Streams. In: Proc. ICDM (2006) 21. : Finding Maximal Frequent Itemsets over Online Data Streams Adaptively. In: Proc. ICDM (2005) 22. : Approximate Frequency Counts over Streaming Data. In: Proc. VLDB (2002) 23. : Verifying and Mining Frequent Patterns from Large Windows over Data Streams. In: Proc. ICDE (2008) 24. : Mining Maximal Frequent Itemsets from Data Streams. Journal of Information Science 33(3), 251–262 (2007) 25.

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Advanced Data Mining and Applications: 7th International Conference, ADMA 2011, Beijing, China, December 17-19, 2011, Proceedings, Part I by Yong-Bin Kang, Shonali Krishnaswamy (auth.), Jie Tang, Irwin King, Ling Chen, Jianyong Wang (eds.)


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