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An effective method for detecting outlying regions in a 2-dimensional array

  • Sookmyung Women's University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

As sensing devices and simulation programs are widely used, a large amount of output data is being generated in the form of a 2-dimensional (2D) array. To facilitate the post data processing, it is of critical importance to find anomalous or outlying elements in that array with little human intervention. In this paper, we propose an effective method for locating outlying regions in a 2D array, in which a group of adjacent elements in its entirety deviate significantly from the entire array. To find such outlying regions, we divide the array into small subarrays and build a regression model for each subarray. We then cluster subarrays that are adjacent to each other and have similar regression models into larger subarrays. After the clustering, we detect relatively small clusters as outlying regions. Our experiments confirm the effectiveness of the proposed method.

Original languageEnglish
Title of host publicationBig Data Applications and Services 2017 - The 4th International Conference on Big Data Applications and Services
EditorsCarson K. Leung, Wookey Lee
PublisherSpringer Verlag
Pages37-41
Number of pages5
ISBN (Print)9789811306945
DOIs
StatePublished - 2019
Event4th International Conference on Big Data Applications and Services, BigDAS 2017 - Tashkent, Uzbekistan
Duration: 15 Aug 201718 Aug 2017

Publication series

NameAdvances in Intelligent Systems and Computing
Volume770
ISSN (Print)2194-5357

Conference

Conference4th International Conference on Big Data Applications and Services, BigDAS 2017
Country/TerritoryUzbekistan
CityTashkent
Period15/08/1718/08/17

Keywords

  • 2-dimensional array analysis
  • Collective outliers
  • Outlier detection

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