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A Multivariate Spatial Outlier Detection Method Based on Semantic Similarity

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Computer Science and Convergence

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 114))

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Abstract

Spatial outlier detection is usually done in local neighbourhoods. We use an interpretable similarity measure to calculate the similarity between the regions of influence of spatial objects using spatial and non spatial attributes and relations both in the semantic description and in the similarity measure. A systematic method for similarity threshold selection is presented that can be used to categorize objects by their behavioral pattern in semantically similar neighborhoods. This paper’s main contribution is developing a multivariate two level outlier detection method. Real world data is used to evaluate our method.

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Author information

Authors and Affiliations

  1. Department of Computer Engineering, University of Isfahan, Isfahan, Iran

    Fatemeh Azam & Ahmad Baraani-Dastjerdi

Authors
  1. Fatemeh Azam
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  2. Ahmad Baraani-Dastjerdi
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Corresponding author

Correspondence to Fatemeh Azam .

Editor information

Editors and Affiliations

  1. SeoulTech, Computer Science and Engineering, Seoul University of Science & Technology, Gongreung 2-dong 172, Seoul, 139-742, Korea, Republic of (South Korea)

    James J. (Jong Hyuk) Park

  2. Inst. Computer Science & Information, Engineering, National Ilan University, 1 Sec. 1, Shen-Lung Rd., I-Lan, 260, Taiwan R.O.C.

    Han-Chieh Chao

  3. , Computer Science & Software Engineering, Monmouth University, W. Long Branch, 07764, USA

    Mohammad S. Obaidat

  4. , Division of e-Business, Kyungnam University, Changwon, Korea, Republic of (South Korea)

    Jongsung Kim

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© 2012 Springer Science+Business Media B.V.

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Azam, F., Baraani-Dastjerdi, A. (2012). A Multivariate Spatial Outlier Detection Method Based on Semantic Similarity. In: J. (Jong Hyuk) Park, J., Chao, HC., S. Obaidat, M., Kim, J. (eds) Computer Science and Convergence. Lecture Notes in Electrical Engineering, vol 114. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-2792-2_21

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  • DOI: https://doi.org/10.1007/978-94-007-2792-2_21

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-2791-5

  • Online ISBN: 978-94-007-2792-2

  • eBook Packages: EngineeringEngineering (R0)

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