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Record Nr. |
UNISA996466195603316 |
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Titolo |
Data Quality and Trust in Big Data [[electronic resource] ] : 5th International Workshop, QUAT 2018, Held in Conjunction with WISE 2018, Dubai, UAE, November 12–15, 2018, Revised Selected Papers / / edited by Hakim Hacid, Quan Z. Sheng, Tetsuya Yoshida, Azadeh Sarkheyli, Rui Zhou |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
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ISBN |
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Edizione |
[1st ed. 2019.] |
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Descrizione fisica |
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1 online resource (IX, 137 p. 45 illus., 19 illus. in color.) |
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Collana |
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Information Systems and Applications, incl. Internet/Web, and HCI ; ; 11235 |
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Disciplina |
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Soggetti |
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Application software |
Information storage and retrieval |
Artificial intelligence |
Computer system failures |
Information Systems Applications (incl. Internet) |
Information Storage and Retrieval |
Artificial Intelligence |
System Performance and Evaluation |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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A Novel Data Quality Metric for Minimality -- Automated Schema Quality Measurement in Large-scale Information Systems -- Email Importance Evaluation in Mailing List Discussions -- SETTRUST: Social Exchange Theory Based Context- Aware Trust Prediction in Online Social Networks -- CNR: Cross-Network Recommendation Embedding User’s Personality -- Firefly Algorithm with Proportional Adjustment Strategy -- A Formal Taxonomy of Temporal Data Defects -- Data-intensive Computing Acceleration with Python in Xilinx FPGA -- Delone and McLean IS Success Model for Evaluating Knowledge Sharing. |
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Sommario/riassunto |
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This book constitutes revised selected papers from the International Workshop on Data Quality and Trust in Big Data, QUAT 2018, which |
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was held in conjunction with the International Conference on Web Information Systems Engineering, WISE 2018, in Dubai, UAE, in November 2018. The 9 papers presented in this volume were carefully reviewed and selected from 15 submissions. They deal with novel ideas and solutions related to the problems of exploring, assessing, monitoring, improving, and maintaining the quality of data and trust for Big Data. |
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