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Advanced Data Mining and Applications 9th International Conference, ADMA 2013, Hangzhou, China, December 14-16, 2013, Proceedings, Part II /

The two-volume set LNAI 8346 and 8347 constitutes the thoroughly refereed proceedings of the 9th International Conference on Advanced Data Mining and Applications, ADMA 2013, held in Hangzhou, China, in December 2013. The 32 regular papers and 64 short papers presented in these two volumes were care...

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Corporate Author: SpringerLink (Online service)
Other Authors: Motoda, Hiroshi. (Editor, http://id.loc.gov/vocabulary/relators/edt), Wu, Zhaohui. (Editor, http://id.loc.gov/vocabulary/relators/edt), Cao, Longbing. (Editor, http://id.loc.gov/vocabulary/relators/edt), Zaiane, Osmar. (Editor, http://id.loc.gov/vocabulary/relators/edt), Yao, Min. (Editor, http://id.loc.gov/vocabulary/relators/edt), Wang, Wei. (Editor, http://id.loc.gov/vocabulary/relators/edt)
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Edition:1st ed. 2013.
Series:Lecture Notes in Artificial Intelligence ; 8347
Subjects:
Artificial intelligence.
Data mining.
Information storage and retrieval.
Artificial Intelligence.
Data Mining and Knowledge Discovery.
Information Storage and Retrieval.
Online Access:https://doi.org/10.1007/978-3-642-53917-6
Summary:The two-volume set LNAI 8346 and 8347 constitutes the thoroughly refereed proceedings of the 9th International Conference on Advanced Data Mining and Applications, ADMA 2013, held in Hangzhou, China, in December 2013. The 32 regular papers and 64 short papers presented in these two volumes were carefully reviewed and selected from 222 submissions. The papers included in these two volumes cover the following topics: opinion mining, behavior mining, data stream mining, sequential data mining, web mining, image mining, text mining, social network mining, classification, clustering, association rule mining, pattern mining, regression, predication, feature extraction, identification, privacy preservation, applications, and machine learning.
Physical Description:XXII, 538 p. 163 illus. online resource.
ISBN:9783642539176

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