Machine Learning and Data Mining in Pattern Recognition: 14th International Conference, MLDM 2018, New York, NY, USA, July 15-19, 2018, Proceedings, Part II - Info and Reading Options
"Machine Learning and Data Mining in Pattern Recognition: 14th International Conference, MLDM 2018, New York, NY, USA, July 15-19, 2018, Proceedings, Part II" was published by Springer International Publishing : Imprint: Springer in 2018 - Cham and it has 1 pages.
“Machine Learning and Data Mining in Pattern Recognition: 14th International Conference, MLDM 2018, New York, NY, USA, July 15-19, 2018, Proceedings, Part II” Metadata:
- Title: ➤ Machine Learning and Data Mining in Pattern Recognition: 14th International Conference, MLDM 2018, New York, NY, USA, July 15-19, 2018, Proceedings, Part II
- Number of Pages: 1
- Publisher: ➤ Springer International Publishing : Imprint: Springer
- Publish Date: 2018
- Publish Location: Cham
“Machine Learning and Data Mining in Pattern Recognition: 14th International Conference, MLDM 2018, New York, NY, USA, July 15-19, 2018, Proceedings, Part II” Subjects and Themes:
- Subjects: ➤ Application software - Artificial intelligence - Data mining - Natural language processing (Computer science) - Artificial Intelligence - Data Mining and Knowledge Discovery - Information Systems Applications (incl. Internet) - Natural Language Processing (NLP) - Natural Language Processing (NLP)
Edition Identifiers:
- ISBN-13: 9783319961330
- All ISBNs: 9783319961330
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"Machine Learning and Data Mining in Pattern Recognition: 14th International Conference, MLDM 2018, New York, NY, USA, July 15-19, 2018, Proceedings, Part II" Description:
Open Data:
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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