Clustering Data Without Distance Functions.

G. D. Ramkumar, Arun N. Swami: Clustering Data Without Distance Functions. IEEE Data Eng. Bull. 21(1): 9-14(1998)
  author    = {G. D. Ramkumar and
               Arun N. Swami},
  title     = {Clustering Data Without Distance Functions},
  journal   = {IEEE Data Eng. Bull.},
  volume    = {21},
  number    = {1},
  year      = {1998},
  pages     = {9-14},
  ee        = {db/journals/debu/RamkumarS98.html},
  bibsource = {DBLP,}


Data mining is being applied with profit in many applications. Clustering or segmentation of data is an important data mining application. One of the problems with traditional clustering methods is that they require the analyst to define distance functions that are not always available. In this paper, we describe a new method for clustering without distance functions.

Copyright © 1998 by The Institute of Electrical and Electronic Engineers, Inc. (IEEE). Abstract used with permission.

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Data Engineering Bulletin March 1998: Mining of Large Datasets (Daniel Barbara, ed.)
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Referenced by

  1. Tadeusz Morzy, Marek Wojciechowski, Maciej Zakrzewicz: Pattern-Oriented Hierachical Clustering. ADBIS 1999: 179-190
  2. San-Yih Hwang, Jeng-Kuen Chiu: Toward Optimal Replication for Hierarchical Location Management in Wireless Systems. ER Workshops 1998: 278-289
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