Data science : 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.Material type: TextSeries: Serienbezeichnung | Lecture notes in computer science ; 9208. | LNCS sublibrary. SL 3, Information systems and applications, incl. Internet/Web, and HCI.Publisher: Cham : Springer, 2015Description: 1 online resource (x, 194 pages) : illustrationsContent type: text Media type: computer Carrier type: online resourceISBN: 9783319244747; 3319244744Other title: ICDS 2015Subject(s): Databases -- Congresses | Computer science | Computer networks | Software engineering | Database management | Information organization | Information retrieval | Pattern perception | Information retrieval | Pattern recognition | Network hardware | Software Engineering | Databases | Computers -- System Administration -- Storage & Retrieval | Computers -- Information Technology | Computers -- Computer Vision & Pattern Recognition | Computers -- Hardware -- Network Hardware | Computers -- Software Development & Engineering -- General | Computers -- Database Management -- General | Computer networks | Computer science | Database management | Databases | Information organization | Information retrieval | Pattern perception | Software engineeringGenre/Form: Electronic books. | Conference papers and proceedings. Additional physical formats: Printed edition:: No titleDDC classification: 005.74 LOC classification: QA76.9.D3Online resources: Click here to access online
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This book constitutes the refereed proceedings of the Second International Conference on Data Science, ICDS 2015, held in Sydney, Australia, in 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.
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.