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Expanding K-Means Algorithm For Absolute Data

Author

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  • Ana-Maria Ramona Stancu

    ()

  • Mihaela Mocanu

    ()

Abstract

In the majority of works published so far on k-means algorithm, the study was performed on numerical data and functions with which the distance between the data points can be calculated. Recently, as far as the clustering issue is concerned, the problem of using absolute data has also been raised, and the algorithms used so far have been considered unacceptable for their implementation in large databases. This article aims to apply accurately the "notion of the cluster center" on a set of absolute objects and how it is used in issues related to absolute objects grouping.

Suggested Citation

  • Ana-Maria Ramona Stancu & Mihaela Mocanu, 2016. "Expanding K-Means Algorithm For Absolute Data," Knowledge Horizons - Economics, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 8(2), pages 163-167, June.
  • Handle: RePEc:khe:journl:v:8:y:2016:i:2:p:163-167
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    More about this item

    Keywords

    Algorithm; center; cluster; data mining; distant; object;

    JEL classification:

    • L8 - Industrial Organization - - Industry Studies: Services

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