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Big Data Analytics and Knowledge Discovery [[electronic resource] ] : 21st International Conference, DaWaK 2019, Linz, Austria, August 26–29, 2019, Proceedings / / edited by Carlos Ordonez, Il-Yeol Song, Gabriele Anderst-Kotsis, A Min Tjoa, Ismail Khalil



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Titolo: Big Data Analytics and Knowledge Discovery [[electronic resource] ] : 21st International Conference, DaWaK 2019, Linz, Austria, August 26–29, 2019, Proceedings / / edited by Carlos Ordonez, Il-Yeol Song, Gabriele Anderst-Kotsis, A Min Tjoa, Ismail Khalil Visualizza cluster
Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Edizione: 1st ed. 2019.
Descrizione fisica: 1 online resource (XIII, 321 p. 164 illus., 80 illus. in color.)
Disciplina: 005.7
Soggetto topico: Database management
Data mining
Arithmetic and logic units, Computer
Computer system failures
Artificial intelligence
Database Management
Data Mining and Knowledge Discovery
Arithmetic and Logic Structures
System Performance and Evaluation
Artificial Intelligence
Persona (resp. second.): OrdonezCarlos
SongIl-Yeol
Anderst-KotsisGabriele
TjoaA Min
KhalilIsmail
Note generali: Includes index.
Nota di contenuto: Applications -- Detecting the Onset of Machine Failure Using Anomaly Detection Methods -- A Hybrid Architecture for Tactical and Strategic Precision Agriculture -- Urban analytics of big transportation data for supporting smart cities -- Patterns -- Frequent Item Mining When Obtaining Support is Costly -- Mining Sequential Pattern of Historical Purchases for E-Commerce Recommendation -- Discovering and Visualizing Efficient Patterns in Cost/Utility Sequences -- Efficient Row Pattern Matching using Pattern Hierarchies for Sequence OLAP -- Statistically Significant Discriminative Patterns Searching -- RDF and Streams -- Multidimensional Integration of RDF datasets -- RDFPartSuite: Bridging Physical and Logical RDF Partitioning -- Mining quantitative temporal dependencies between interval-based streams -- Democratization of OLAP DSMS -- Big Data Systems -- Leveraging the Data Lake - Current State and Challenges -- SDWP: A New Data Placement Strategy for Distributed Big Data Warehouses in Hadoop -- Improved Programming-Language Independent MapReduce on Shared-Memory Systems -- Evaluating Redundancy and Partitioning of Geospatial Data in Document-Oriented Data Warehouses -- Graphs and Machine Learning -- Scalable Least Square Twin Support Vector Machine Learning -- Finding Strongly Correlated Trends in Dynamic Attributed Graphs -- Text-based Event Detection: Deciphering Date Information Using Graph Embeddings -- Efficiently Computing Homomorphic Matches of Hybrid Pattern Queries on Large Graphs -- Databases -- From Conceptual to Logical ETL Design using BPMN and Relational Algebra -- Accurate Aggregation Query-Result Estimation and Its Efficient Processing on Distributed Key-Value Store.
Sommario/riassunto: This book constitutes the refereed proceedings of the 21st International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2019, held in Linz, Austria, in September 2019. The 12 full papers and 10 short papers presented were carefully reviewed and selected from 61 submissions. The papers are organized in the following topical sections: Applications; patterns; RDF and streams; big data systems; graphs and machine learning; databases.
Titolo autorizzato: Big data analytics and knowledge discovery  Visualizza cluster
ISBN: 3-030-27520-5
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910349305303321
Lo trovi qui: Univ. Federico II
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Serie: Information Systems and Applications, incl. Internet/Web, and HCI ; ; 11708