Machine Learning and Data Mining in Pattern Recognition 9th International Conference, MLDM 2013, New York, NY, USA, July 19-25, 2013, Proceedings /
Machine Learning and Data Mining in Pattern Recognition 9th International Conference, MLDM 2013, New York, NY, USA, July 19-25, 2013, Proceedings / [electronic resource] :
edited by Petra Perner.
- 1st ed. 2013.
- XII, 660 p. 199 illus. online resource.
- Lecture Notes in Artificial Intelligence, 7988 2945-9141 ; .
- Lecture Notes in Artificial Intelligence, 7988 .
Theoretical topics for classification -- Clustering -- Association rule and pattern mining.- Specific data mining methods for the different multimedia data types.- Image mining -- Text mining -- Video mining.-Web mining.
This book constitutes the refereed proceedings of the 9th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2013, held in New York, USA in July 2013. The 51 revised full papers presented were carefully reviewed and selected from 212 submissions. The papers cover the topics ranging from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and web mining.
9783642397127
10.1007/978-3-642-39712-7 doi
Artificial intelligence.
Data mining.
Pattern recognition systems.
Algorithms.
Artificial Intelligence.
Data Mining and Knowledge Discovery.
Automated Pattern Recognition.
Algorithms.
Q334-342 TA347.A78
006.3
Theoretical topics for classification -- Clustering -- Association rule and pattern mining.- Specific data mining methods for the different multimedia data types.- Image mining -- Text mining -- Video mining.-Web mining.
This book constitutes the refereed proceedings of the 9th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2013, held in New York, USA in July 2013. The 51 revised full papers presented were carefully reviewed and selected from 212 submissions. The papers cover the topics ranging from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and web mining.
9783642397127
10.1007/978-3-642-39712-7 doi
Artificial intelligence.
Data mining.
Pattern recognition systems.
Algorithms.
Artificial Intelligence.
Data Mining and Knowledge Discovery.
Automated Pattern Recognition.
Algorithms.
Q334-342 TA347.A78
006.3