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Database and Expert Systems Applications: Lecture Notes in Computer Science, cartea 10439

Editat de Djamal Benslimane, Ernesto Damiani, William I. Grosky, Abdelkader Hameurlain, Amit Sheth, Roland R. Wagner
en Limba Engleză Paperback – 2 aug 2017
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 Classific
ation.
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Specificații

ISBN-13: 9783319644707
ISBN-10: 331964470X
Pagini: 488
Ilustrații: XXIV, 461 p. 157 illus.
Dimensiuni: 155 x 235 x 27 mm
Greutate: 0.73 kg
Ediția:1st edition 2017
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science

Locul publicării:Cham, Switzerland

Cuprins

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.

Caracteristici

Includes supplementary material: sn.pub/extras