{"product_id":"9783030275198","title":"Big Data Analytics and Knowledge Discovery : 21st International Conference, DaWaK 2019, Linz, Austria, August 26-29, 2019, Proceedings (Lecture Notes in Computer Science .11708) (1st ed. 2019. 2019. xiii, 321 S. 84 SW-Abb., 80 Farbabb. 235 mm)","description":"\u003cp\u003eThis 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.\u003c\/p\u003e\u003cp\u003eThe 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.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eApplications.-\u003c\/b\u003e 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.- \u003cb\u003ePatterns.-\u003c\/b\u003e 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.- \u003cb\u003eRDF and Streams.-\u003c\/b\u003e Multidimensional Integration of RDF datasets.- RDFPartSuite: Bridging Physical and Logical RDF Partitioning.- Mining quantitative temporal dependencies between interval-based streams.- Democratization of OLAP DSMS.- \u003cb\u003eBig Data Systems.-\u003c\/b\u003e Leveraging the Data Lake - Current State and Challenges.- SDWP: A New Data Placement Strategy for Distributed Big DataWarehouses in Hadoop.- Improved Programming-Language Independent MapReduce on Shared-Memory Systems.- Evaluating Redundancy and Partitioning of Geospatial Data in Document-Oriented Data Warehouses.- \u003cb\u003eGraphs and Machine Learning.-\u003c\/b\u003e 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.- \u003cb\u003eDatabases.-\u003c\/b\u003e 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.\u003cb\u003e\u003c\/b\u003e\u003c\/p\u003e","brand":"SPRINGER, BERLIN; SPRINGER INTERNATIONAL PUBLISHING;","offers":[{"title":"Default Title","offer_id":48814770585835,"sku":"00000_00000_00000_00000","price":93.8,"currency_code":"SGD","in_stock":false}],"url":"https:\/\/kinokuniya.com.sg\/products\/9783030275198","provider":"Books Kinokuniya Singapore","version":"1.0","type":"link"}