Chrological Big data Curation: A Study on the Enhanced Information Retrieval Systemopen access
- Authors
- Choi, Seungjin; Seo, Jiwan; Kim, Mucheol; Kang, Sunghyun; Han, Sangyong
- Issue Date
- Dec-2017
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Information retrieval; big data; curation; chronological order
- Citation
- IEEE ACCESS, v.5, pp 11269 - 11277
- Pages
- 9
- Journal Title
- IEEE ACCESS
- Volume
- 5
- Start Page
- 11269
- End Page
- 11277
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/6249
- DOI
- 10.1109/ACCESS.2016.2642979
- ISSN
- 2169-3536
- Abstract
- In the modern days of big data, the curation of data has become more and more important, especially for handling high volume and complex data systems. With data volumes growing exponentially, along with the increasing variety and heterogeneity of data sources, acquiring the data you may need for analysis has become a costly and time-consuming process. Multiple data sets from various sources must be first processed and connected before they can be used by big data analytics tools. Publication and presentation of data analytics are also very important. However, traditional data curation systems are not designed for this purpose and there is no consideration on the chronological values. Another limitation is that they are usually designed for programmers, not for the ordinary users. In this paper, we propose Chronological Big data Curation system. In the proposed system, acquisition and care of data are processed on the basis of relations between specific topics and chronological order to ensure that data maintains its value over time. The system is implemented and experimental results show the goodness of the proposed system.
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Collections - College of Software > School of Computer Science and Engineering > 1. Journal Articles
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