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Advanced Data Mining and Applications: 8th International Conference, ADMA 2012, Nanjing, China, December 15-18, 2012. Proceedings

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Authors and Corporations: Zhou, Shuigeng (Author), Zhang, Songmao (Other), Karypis, George (Other)
Title: Advanced Data Mining and Applications: 8th International Conference, ADMA 2012, Nanjing, China, December 15-18, 2012. Proceedings/ edited by Shuigeng Zhou, Songmao Zhang, George Karypis
Type of Resource: E-Book Conference Proceedings
Language: English
published:
Berlin, Heidelberg Springer 2012
Series: SpringerLink
Lecture notes in computer science ; 7713
Subjects:
Buchausg. u.d.T.: Advanced data mining and applications, Berlin : Springer, 2012, XVIII, 795 S.
Source: Verbunddaten SWB
Access Information: Elektronischer Volltext - Campuslizenz
Description
Abstract: Social Media Mining -- Clustering -- Machine Learning: Algorithms and Applications -- Classification -- Prediction, Regression and Recognition -- Optimization and Approximation -- Mining Time Series and Streaming Data -- Web Mining and Semantic Analysis -- Data Mining Applications -- Search and Retrieval -- Information Recommendation and Hiding -- Outlier Detection -- Topic Modeling -- Data Cube Computing.
This book constitutes the refereed proceedings of the 8th International Conference on Advanced Data Mining and Applications, ADMA 2012, held in Nanjing, China, in December 2012. The 32 regular papers and 32 short papers presented in this volume were carefully reviewed and selected from 168 submissions. They are organized in topical sections named: social media mining; clustering; machine learning: algorithms and applications; classification; prediction, regression and recognition; optimization and approximation; mining time series and streaming data; Web mining and semantic analysis; data mining applications; search and retrieval; information recommendation and hiding; outlier detection; topic modeling; and data cube computing.
Physical Description: Online-Ressource (XVIII, 795 p. 287 illus, digital)
ISBN: 9783642355271
DOI: 10.1007/978-3-642-35527-1