Machine Learning and Data Mining in Pattern Recognition 10th International Conference, MLDM 2014, St. Petersburg, Russia, July 21-24, 2014. Proceedings / [electronic resource] :
edited by Petra Perner.
- XIV, 536 p. 188 illus. online resource.
- Lecture Notes in Computer Science, 8556 0302-9743 ; .
- Lecture Notes in Computer Science, 8556 .
Theoretical topics for classification -- Clustering -- Association rule.- 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 10th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2014, held in St. Petersburg, Russia in July 2014. The 40 full papers presented were carefully reviewed and selected from 128 submissions. The topics range 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.
9783319089799
10.1007/978-3-319-08979-9 doi
Computer science.
Algorithms.
Database management.
Data mining.
Artificial intelligence.
Pattern recognition.
Computer Science.
Artificial Intelligence (incl. Robotics).
Data Mining and Knowledge Discovery.
Pattern Recognition.
Algorithm Analysis and Problem Complexity.
Information Systems Applications (incl. Internet).
Database Management.
Q334-342 TJ210.2-211.495
006.3
Theoretical topics for classification -- Clustering -- Association rule.- 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 10th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2014, held in St. Petersburg, Russia in July 2014. The 40 full papers presented were carefully reviewed and selected from 128 submissions. The topics range 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.
9783319089799
10.1007/978-3-319-08979-9 doi
Computer science.
Algorithms.
Database management.
Data mining.
Artificial intelligence.
Pattern recognition.
Computer Science.
Artificial Intelligence (incl. Robotics).
Data Mining and Knowledge Discovery.
Pattern Recognition.
Algorithm Analysis and Problem Complexity.
Information Systems Applications (incl. Internet).
Database Management.
Q334-342 TJ210.2-211.495
006.3