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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
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← Back to VOLUME 6, ISSUE 2, FEBRUARY 2017

Accurate Detection of Unusual Event in Network Data Stream (Outlier)

Priti G. Manekar, Prof. Pravin G. Kulurkar

DOI: 10.17148/IJARCCE.2017.6254

Abstract: Outlier Mining is an important task of discovering the data records which have an exceptional behavior comparing with other records in the remaining dataset. Outliers do not follow with other data objects in the dataset. There are many effective approaches to detect outliers in numerical data. Most of the earliest work on outlier detection was performed by the statistics community on numeric data. But for categorical dataset there are limited approaches By using memory efficient incremental local outlier (MiLOF) detection algorithm and ROAD (Ranking-based Outlier Analysis and Detection algorithm).



Keywords: Outlier detection, Stream data mining, Local outlier, Memory efficiency.

How to Cite:

[1] Priti G. Manekar, Prof. Pravin G. Kulurkar, “Accurate Detection of Unusual Event in Network Data Stream (Outlier),” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2017.6254