Next-Generation Big Data Analytics: State of the Art, Challenges, and Future Research Topics
- Authors
- Lv, Zhihan; Song, Houbing; Basanta-Val, Pablo; Steed, Anthony; Jo, Minho
- Issue Date
- 8월-2017
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Big data; massive data; network
- Citation
- IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, v.13, no.4, pp.1891 - 1899
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
- Volume
- 13
- Number
- 4
- Start Page
- 1891
- End Page
- 1899
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/82654
- DOI
- 10.1109/TII.2017.2650204
- ISSN
- 1551-3203
- Abstract
- The term big data occurs more frequently now than ever before. A large number of fields and subjects, ranging from everyday life to traditional research fields (i.e., geography and transportation, biology and chemistry, medicine and rehabilitation), involve big data problems. The popularizing of various types of network has diversified types, issues, and solutions for big data more than ever before. In this paper, we review recent research in data types, storage models, privacy, data security, analysis methods, and applications related to network big data. Finally, we summarize the challenges and development of big data to predict current and future trends.
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Collections - Graduate School > Department of Computer and Information Science > 1. Journal Articles
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