Database and Expert Systems Applications

28th International Conference, DEXA 2017, Lyon, France, August 28-31, 2017, Proceedings, Part I
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ISBN-13:
9783319644677
Veröffentl:
2017
Einband:
Paperback
Erscheinungsdatum:
01.08.2017
Seiten:
544
Autor:
Djamal Benslimane
Gewicht:
814 g
Format:
235x155x30 mm
Serie:
10438, Information Systems and Applications, incl. Internet/Web, and HCI
Sprache:
Englisch
Beschreibung:

This two volume set LNCS 10438 and LNCS 10439 constitutes the refereed proceedings of the 28th International Conference on Database and Expert Systems Applications, DEXA 2017, held in Lyon, France, August 2017.The 37 revised full papers presented together with 40 short papers were carefully reviewed and selected from 166 submissions. The papers discuss a range of topics including: Semantic Web and Semantics; Graph Matching; Data Modeling, Data Abstraction, and Uncertainty; Preferences and Query Optimization; Data Integration and RDF Matching; Security and Privacy; Web Search; Data Clustering; Top-K and Skyline Queries; Data Mining and Big Data; Service Computing; Continuous and Temporal Data, and Continuous Query Language; Text Processing and Semantic Search; Indexing and Concurrency Control Methods; Data Warehouse and Data Stream Warehouse; Data Mining and Machine Learning; Recommender Systems and Query Recommendation; Graph Algorithms; Semantic Clustering and Data Classification.
Includes supplementary material: sn.pub/extras
Semantic Web and Semantics.- Graph Matching.- Data Modeling, Data Abstraction, and Uncertainty.- Preferences and Query Optimization.- Data Integration and RDF Matching.- Security and Privacy.- Web Search.- Data Clustering.- Top-K and Skyline Queries.- Data Mining and Big Data.- Service Computing.- Continuous and Temporal Data, and Continuous Query Language.- Text Processing and Semantic Search.- Indexing and Concurrency Control Methods.- Data Warehouse and Data Stream Warehouse.- Data Mining and Machine Learning.- Recommender Systems and Query Recommendation.- Graph Algorithms.- Semantic Clustering and Data Classification.

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