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Machine Learning and Data Mining in Pattern Recognition
(Englisch)
14th International Conference, MLDM 2018, New York, NY, USA, July 15-19, 2018, Proceedings, Part II
Perner, Petra

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Machine Learning and Data Mining in Pattern Recognition

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  • 231670869

Produktbeschreibung

This two-volume set LNAI 10934 and LNAI 10935 constitutes the refereed proceedings of the 14th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2018, held in New York, NY, USA in July 2018. 
The 92 regular papers presented in this two-volume set were carefully reviewed and selected from 298 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as  image mining, text mining, video mining, and Web mining.



Classification.- Clustering.- Image mining.- Text mining.- Video mining.-Web mining.- Graph mining.- Process mining.

This two-volume set LNAI 10934 and LNAI 10935 constitutes the refereed proceedings of the 14th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2018, held in New York, NY, USA in July 2018. 
The 92 regular papers presented in this two-volume set were carefully reviewed and selected from 298 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as  image mining, text mining, video mining, and Web mining.





Inhaltsverzeichnis

Classification.- Clustering.- Image mining.- Text mining.- Video mining.-Web mining.- Graph mining.- Process mining.


Klappentext

This two-volume set LNAI 10934 and LNAI 10935 constitutes the refereed proceedings of the 14th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2018, held in New York, NY, USA in July 2018.
The 92 regular papers presented in this two-volume set were carefully reviewed and selected from 298 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.



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