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Record Nr. |
UNISA996466306603316 |
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Titolo |
Data Science [[electronic resource] ] : Second International Conference, ICDS 2015, Sydney, Australia, August 8-9, 2015, Proceedings / / edited by Chengqi Zhang, Wei Huang, Yong Shi, Philip S. Yu, Yangyong Zhu, Yingjie Tian, Peng Zhang, Jing He |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
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ISBN |
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Edizione |
[1st ed. 2015.] |
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Descrizione fisica |
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1 online resource (X, 194 p. 60 illus. in color.) |
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Collana |
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Information Systems and Applications, incl. Internet/Web, and HCI ; ; 9208 |
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Disciplina |
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Soggetti |
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Database management |
Information storage and retrieval |
Application software |
Pattern recognition |
Computer communication systems |
Software engineering |
Database Management |
Information Storage and Retrieval |
Information Systems Applications (incl. Internet) |
Pattern Recognition |
Computer Communication Networks |
Software Engineering |
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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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Note generali |
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Bibliographic Level Mode of Issuance: Monograph |
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Nota di contenuto |
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Mathematical issues in data science -- Big data issues and applications -- Data quality and data preparation -- Data-driven scientific research -- Evaluation and measurement in data service -- Big data mining and knowledge management.- case study of data science -- Social impacts of data science. |
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Sommario/riassunto |
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This book constitutes the refereed proceedings of the Second International Conference on Data Science, ICDS 2015, held in Sydney, |
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Australia, during August 8-9, 2015. The 19 revised full papers and 5 short papers presented were carefully reviewed and selected from 31 submissions. The papers focus on the following topics: mathematical issues in data science; big data issues and applications; data quality and data preparation; data-driven scientific research; evaluation and measurement in data service; big data mining and knowledge management; case study of data science; social impacts of data science. |
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