New Frontiers in Mining Complex Patterns Second International Workshop, NFMCP 2013, Held in Conjunction with ECML-PKDD 2013, Prague, Czech Republic, September 27, 2013, Revised Selected Papers / [electronic resource] :
edited by Annalisa Appice, Michelangelo Ceci, Corrado Loglisci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras.
- XII, 261 p. 80 illus. online resource.
- Lecture Notes in Computer Science, 8399 0302-9743 ; .
- Lecture Notes in Computer Science, 8399 .
Data Streams and and Time Series Analysis -- Classification, Clustering and Pattern Discovery -- Graphs, Networks and Relational Data -- Machine Learning and Music Data.
This book constitutes the thoroughly refereed post-conference proceedings of the Second International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2013, held in conjunction with ECML/PKDD 2013 in Prague, Czech Republic, in September 2013. The 16 revised full papers were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on data streams and time series analysis, classification, clustering and pattern discovery, graphs, networks and relational data, machine learning and music data.
9783319084077
10.1007/978-3-319-08407-7 doi
Computer science.
Database management.
Data mining.
Information storage and retrieval.
Artificial intelligence.
Computer Science.
Data Mining and Knowledge Discovery.
Database Management.
Information Storage and Retrieval.
Artificial Intelligence (incl. Robotics).
QA76.9.D343
006.312
Data Streams and and Time Series Analysis -- Classification, Clustering and Pattern Discovery -- Graphs, Networks and Relational Data -- Machine Learning and Music Data.
This book constitutes the thoroughly refereed post-conference proceedings of the Second International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2013, held in conjunction with ECML/PKDD 2013 in Prague, Czech Republic, in September 2013. The 16 revised full papers were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on data streams and time series analysis, classification, clustering and pattern discovery, graphs, networks and relational data, machine learning and music data.
9783319084077
10.1007/978-3-319-08407-7 doi
Computer science.
Database management.
Data mining.
Information storage and retrieval.
Artificial intelligence.
Computer Science.
Data Mining and Knowledge Discovery.
Database Management.
Information Storage and Retrieval.
Artificial Intelligence (incl. Robotics).
QA76.9.D343
006.312