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Data streams oriented outlier detection method : a fast minimal infrequent pattern mining
Joint Authors
Source
The International Arab Journal of Information Technology
Issue
Vol. 18, Issue 6 (30 Nov. 2021), pp.864-870, 7 p.
Publisher
Zarqa University Deanship of Scientific Research
Publication Date
2021-11-30
Country of Publication
Jordan
No. of Pages
7
Main Subjects
Information Technology and Computer Science
Abstract EN
Outlier detection is a common method for analyzing data streams.
In the existing outlier detection methods, most of methods compute distance of points to solve certain specific outlier detection problems.
However, these methods are computationally expensive and cannot process data streams quickly.
The outlier detection method based on pattern mining resolves the aforementioned issues, but the existing methods are inefficient and cannot meet requirements of quickly mining data streams.
In order to improve the efficiency of the method, a new outlier detection method is proposed in this paper.
First, a fast minimal infrequent pattern mining method is proposed to mine the minimal infrequent pattern from data streams.
Second, an efficient outlier detection algorithm based on minimal infrequent pattern is proposed for detecting the outliers in the data streams by mining minimal infrequent pattern.
The algorithm proposed in this paper is demonstrated by real telemetry data of a satellite in orbit.
The experimental results show that the proposed method not only can be applied to satellite outlier detection, but also is superior to the existing methods.
American Psychological Association (APA)
Zhou, Zhongyu& Pi, Dechang. 2021. Data streams oriented outlier detection method : a fast minimal infrequent pattern mining. The International Arab Journal of Information Technology،Vol. 18, no. 6, pp.864-870.
https://search.emarefa.net/detail/BIM-1430960
Modern Language Association (MLA)
Zhou, Zhongyu& Pi, Dechang. Data streams oriented outlier detection method : a fast minimal infrequent pattern mining. The International Arab Journal of Information Technology Vol. 18, no. 6 (Nov. 2021), pp.864-870.
https://search.emarefa.net/detail/BIM-1430960
American Medical Association (AMA)
Zhou, Zhongyu& Pi, Dechang. Data streams oriented outlier detection method : a fast minimal infrequent pattern mining. The International Arab Journal of Information Technology. 2021. Vol. 18, no. 6, pp.864-870.
https://search.emarefa.net/detail/BIM-1430960
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 869
Record ID
BIM-1430960