Meny
 
Big Data Analytics and Knowledge Discovery - 
      Carlos Ordonez
    
      Il-Yeol Song
    
      Gabriele Anderst-Kotsis
    
      A Min Tjoa
    
      Ismail Khalil

Big Data Analytics and Knowledge Discovery

21st International Conference, DaWaK 2019, Linz, Austria, August 26–29, 2019, Proceedings

Carlos Ordonez (Redaktør) ; Il-Yeol Song (Redaktør) ; Gabriele Anderst-Kotsis (Redaktør) ; A Min Tjoa (Redaktør) ; Ismail Khalil (Redaktør)

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. Les mer
Vår pris
844,-

(Paperback) Fri frakt!
Leveringstid: Usikker levering*
*Vi bestiller varen fra forlag i utlandet. Dersom varen finnes, sender vi den så snart vi får den til lager

Paperback
Legg i
Paperback
Legg i
Vår pris: 844,-

(Paperback) Fri frakt!
Leveringstid: Usikker levering*
*Vi bestiller varen fra forlag i utlandet. Dersom varen finnes, sender vi den så snart vi får den til lager

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.
FAKTA
Utgitt:
Forlag: Springer Nature Switzerland AG
Innbinding: Paperback
Språk: Engelsk
Sider: 321
ISBN: 9783030275198
Format: 24 x 16 cm
KATEGORIER:

Bla i alle kategorier

VURDERING
Gi vurdering
Les vurderinger
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.