Frequent pattern-based outlier detection measurements: A survey

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
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

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