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Web and Big Data
Details
This two volume set, LNCS 10366 and 10367, constitutes the thoroughly refereed proceedings of the First International Joint Conference, APWeb-WAIM 2017, held in Beijing, China in July 2017.
The 44 full papers presented together with 32 short papers and 10 demonstrations papers were carefully reviewed and selected from 240 submissions. The papers are organized around the following topics: spatial data processing and data quality; graph data processing; data mining, privacy and semantic analysis; text and log data management; social networks; data mining and data streams; query processing; topic modeling; machine learning; recommendation systems; distributed data processing and applications; machine learning and optimization.
Includes supplementary material: sn.pub/extras
Klappentext
This two -volume set, LNCS 10366 and 10367, constitutes the thoroughly refereed proceedings of the First International Joint Conference, APWeb-WAIM 2017, held in Beijing, China in July 2017. The 44 full papers presented together with 32 short papers and 10 demonstrations papers were carefully reviewed and selected from 240 submissions. The papers are organized around the following topics: spatial data processing and data quality; graph data processing; data mining, privacy and semantic analysis; text and log data management; social networks; data mining and data streams; query processing; topic modeling; machine learning; recommendation systems; distributed data processing and applications; machine learning and optimization.
Inhalt
Spatial data processing and data quality.- Graph data processing.- Data mining, privacy and semantic analysis.- Text and log data management.-Social networks.- Data mining and data streams.- Query processing.- Topic modeling.- Machine learning.- Recommendation systems.- Distributed data processing and applications.- Machine learning and optimization. ****
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783319635637
- Genre Information Technology
- Auflage 1st ed. 2017
- Editor Lei Chen, Christian S. Jensen, Cyrus Shahabi, Xiaochun Yang, Xiang Lian
- Lesemotiv Verstehen
- Anzahl Seiten 362
- Größe H23mm x B156mm x T236mm
- Jahr 2017
- EAN 9783319635637
- Format Kartonierter Einband
- ISBN 978-3-319-63563-7
- Titel Web and Big Data
- Untertitel First International Joint Conference, APWeb-WAIM 2017, Beijing, China, July 7-9, 2017, Proceedings, Part II
- Gewicht 581g
- Herausgeber Springer
- Sprache Englisch