Brahim Belhaouari Samir, BBS (2011) Frequent pattern-based outlier detection measurements: A survey. 32. IEEE International Conference on Research and Innovation Systems .
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Abstract
Outlier detection is one of the main data mining tasks. The outliers in data are more significant and interesting than common ones in a wide variety of application domains. Recently, a new trend for detecting the outlier by discovering frequent patterns (or frequent itemsets) from the data set has been studies. In this paper, we present a summarization study of the available outlier detection measurements which are based on the frequent patterns discovery.
Item Type: | Article |
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Impact Factor: | IEEE, ISI, SCOPUS |
Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Departments / MOR / COE: | Research Institutes > Megacities Research Institutes > Institute for Health Analytics Departments > Fundamental & Applied Sciences |
Depositing User: | Dr Samir Brahim Belhaouari |
Date Deposited: | 12 Dec 2011 07:25 |
Last Modified: | 19 Jan 2017 08:22 |
URI: | http://scholars.utp.edu.my/id/eprint/7144 |