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03508nam a22006135i 4500 |
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978-3-642-23783-6 |
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DE-He213 |
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20161229111242.0 |
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cr nn 008mamaa |
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110817s2011 gw | s |||| 0|eng d |
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|a 9783642237836
|9 978-3-642-23783-6
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|a 10.1007/978-3-642-23783-6
|2 doi
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|d GrThAP
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|a Machine Learning and Knowledge Discovery in Databases
|h [electronic resource] :
|b European Conference, ECML PKDD 2011, Athens, Greece, September 5-9, 2011, Proceedings, Part II /
|c edited by Dimitrios Gunopulos, Thomas Hofmann, Donato Malerba, Michalis Vazirgiannis.
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2011.
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| 300 |
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|a XXII, 681 p. 163 illus., 113 illus. in color.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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|a text file
|b PDF
|2 rda
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|a Lecture Notes in Computer Science,
|x 0302-9743 ;
|v 6912
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|a This three-volume set LNAI 6911, LNAI 6912, and LNAI 6913 constitutes the refereed proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2011, held in Athens, Greece, in September 2011. The 121 revised full papers presented together with 10 invited talks and 11 demos in the three volumes, were carefully reviewed and selected from about 600 paper submissions. The papers address all areas related to machine learning and knowledge discovery in databases as well as other innovative application domains such as supervised and unsupervised learning with some innovative contributions in fundamental issues; dimensionality reduction, distance and similarity learning, model learning and matrix/tensor analysis; graph mining, graphical models, hidden markov models, kernel methods, active and ensemble learning, semi-supervised and transductive learning, mining sparse representations, model learning, inductive logic programming, and statistical learning. a significant part of the papers covers novel and timely applications of data mining and machine learning in industrial domains.
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| 650 |
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|a Computer science.
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| 650 |
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|a Algorithms.
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| 650 |
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|a Mathematical logic.
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| 650 |
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|a Mathematical statistics.
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| 650 |
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|a Database management.
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| 650 |
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|a Information storage and retrieval.
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| 650 |
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|a Artificial intelligence.
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| 650 |
1 |
4 |
|a Computer Science.
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| 650 |
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|a Artificial Intelligence (incl. Robotics).
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| 650 |
2 |
4 |
|a Database Management.
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| 650 |
2 |
4 |
|a Information Storage and Retrieval.
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| 650 |
2 |
4 |
|a Mathematical Logic and Formal Languages.
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| 650 |
2 |
4 |
|a Algorithm Analysis and Problem Complexity.
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| 650 |
2 |
4 |
|a Probability and Statistics in Computer Science.
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| 700 |
1 |
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|a Gunopulos, Dimitrios.
|e editor.
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| 700 |
1 |
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|a Hofmann, Thomas.
|e editor.
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| 700 |
1 |
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|a Malerba, Donato.
|e editor.
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| 700 |
1 |
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|a Vazirgiannis, Michalis.
|e editor.
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| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
0 |
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|t Springer eBooks
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| 776 |
0 |
8 |
|i Printed edition:
|z 9783642237829
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| 830 |
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|a Lecture Notes in Computer Science,
|x 0302-9743 ;
|v 6912
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| 856 |
4 |
0 |
|u http://dx.doi.org/10.1007/978-3-642-23783-6
|z Full Text via HEAL-Link
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| 912 |
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|a ZDB-2-SCS
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| 912 |
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|a ZDB-2-LNC
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| 950 |
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|a Computer Science (Springer-11645)
|
