Applying clustering analysis on grouping similar OLAP reports

Kevin Chihcheng Hsu, Ming Zhong Li

研究成果: 書貢獻/報告類型會議論文篇章同行評審

1 引文 斯高帕斯(Scopus)

摘要

On Line Analysis Processing (OLAP) is a common solution that modern enterprises use to generate, monitor, share, and administrate their analysis reports. When daily, weekly, and/or monthly reports are generated or published by the OLAP operators, the report readers can only rely on their smart eyes to find out hidden rules, similar reports, or trend inside the potentially huge amount of reports. Data mining is a well-developed field for finding hidden rules inside the data itself. However, there is few techniques focus on finding hidden rules, similarity, or trend using OLAP reports as the unit of analysis. In this paper, we explore how to use clustering analysis on OLAP reports in order to automatically and effectively find the grouping knowledge of OLAP reports. We also address the appropriate presentation of this grouping knowledge to OLAP users.

原文???core.languages.en_GB???
主出版物標題2010 2nd International Conference on Computer Engineering and Applications, ICCEA 2010
頁面417-423
頁數7
DOIs
出版狀態已出版 - 2010
事件2nd International Conference on Computer Engineering and Applications, ICCEA 2010 - , Indonesia
持續時間: 19 3月 201021 3月 2010

出版系列

名字2010 2nd International Conference on Computer Engineering and Applications, ICCEA 2010
2

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???event.eventtypes.event.conference???2nd International Conference on Computer Engineering and Applications, ICCEA 2010
國家/地區Indonesia
期間19/03/1021/03/10

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