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Web and Big Data
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Web and Big Data : APWeb-WAIM 2019 International Workshops, KGMA and DSEA, Chengdu, China, August 1–3, 2019, Revised Selected Papers

2019 ed.

Book Details

Format Paperback / Softback
Book Series Information Systems and Applications, incl. Internet/Web, and HCI
ISBN-10 3030339815
ISBN-13 9783030339814
Edition 2019 ed.
Publisher Springer Nature Switzerland AG
Imprint Springer Nature Switzerland AG
Country of Manufacture GB
Country of Publication GB
Publication Date Nov 1st, 2019
Print length 117 Pages
Product Classification: Educational equipment & technology, computer-aided learning (CAL) Business applications Data warehousing Information retrieval Artificial intelligence
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This book constitutes the thoroughly refereed post-conference proceedings of the Third APWeb-WAIM 2019 Workshops, held jointly with the Third International Joint Conference APWeb-WAIM 2019 in Macau, China, in August 2019. The 8 full papers presented together with 1 invited talk were carefully reviewed and selected from 18 submissions. The papers originating from two workshops, KGMA and DSEA, present cutting-edge ideas, results, experiences, techniques, and tools from all aspects of the management, analysis, and application of knowledge graphs in different domains, as well as theoretical foundations, algorithms, systems, models and applications for big data management and mining.

This book constitutes the thoroughly refereed post-conference proceedings of the Third APWeb-WAIM 2019 Workshops, held jointly with the Third International Joint Conference APWeb-WAIM 2019 in Macau, China, in August 2019.

The 8 full papers presented together with 1 invited talk were carefully reviewed and selected from 18 submissions. The papers originating from two workshops, KGMA and DSEA, present cutting-edge ideas, results, experiences, techniques, and tools from all aspects of the management, analysis, and application of knowledge graphs in different domains, as well as theoretical foundations, algorithms, systems, models and applications for big data management and mining.

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