Spatio-temporal outlier detection in large databases

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Birant D., Kut R. A.

Journal of Computing and Information Technology, cilt.14, sa.4, ss.291-297, 2006 (Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 14 Sayı: 4
  • Basım Tarihi: 2006
  • Doi Numarası: 10.2498/cit.2006.04.04
  • Dergi Adı: Journal of Computing and Information Technology
  • Derginin Tarandığı İndeksler: Scopus, Applied Science & Technology Source, Central & Eastern European Academic Source (CEEAS), Compendex, Computer & Applied Sciences, INSPEC, Library and Information Science Abstracts, Directory of Open Access Journals, Library, Information Science & Technology Abstracts (LISTA)
  • Sayfa Sayıları: ss.291-297
  • Anahtar Kelimeler: Data warehouse, Datamining, Outlier detection, Spatio-temporal data
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

Outlier detection is one of the major data mining methods. This paper proposes a three-step approach to detect spatio-temporal outliers in large databases. These steps are clustering, checking spatial neighbors, and checking temporal neighbors. In this paper, we introduce a new outlier detection algorithm to find small groups of data objects that are exceptional when compared with the remaining large amount of data. In contrast to the existing outlier detection algorithms, the new algorithm has the ability of discovering outliers according to the non-spatial, spatial and temporal values of the objects. In order to demonstrate the new algorithm, this paper also presents an example of application using a data warehouse.