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A Efficient Clustering OLAP Analysis in Big Data Streams Environment
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빅데이터 스트림 환경에서 효율적인 군집 OLAP 분석 기법

논문 기본 정보

Type
Academic journal
Author
Ho-Jin Woo (연세대학교)
Journal
The Society of Convergence Knowledge The Society of Convergence Knowledge Transactions Vol.3 No.2 KCI Accredited Journals
Published
2015.7
Pages
1 - 7 (7page)

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A Efficient Clustering OLAP Analysis in Big Data Streams Environment
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Abstract· Keywords

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With the development of data warehouse system, an OLAP (Online Analytical Processing) has been evolved as an essential tool for data analysts and decision makers. However, it is not feasible to apply the previous data models to the big data computing environments, such as the smart phones and social network services, The big data is generated with the huge volume and the rapid rate, so that it is necessary to group the attribute values of the data efficiently. In order to process such a big data stream, the areas of a user`s interest should be predefined to confined to confine areas but it cannot be employed to the data stream environment because of low performance. To cope with this drawback, this paper proposes a multi-dimensional clustering OLAP method based on the data cube model for dynamically grouping a set of attributes values effectively. The proposed method can reduce the required memory space and the running time for processing and analyzing the multi-dimensional data stream, even though the accuracy of operations may become decreased slightly.
#Big data streams #OLAP #Data cube #Multi-dimensional clustering cuboid

Contents

요약
ABSTRACT
Ⅰ. 서론
Ⅱ. 관련연구
Ⅲ. 군집화 기반 OLAP 분석
Ⅳ. 성능 평가
Ⅴ. 결론
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