An Improvement Of Efficiency For kNN By Using A Heuristic


The KIPS Transactions:PartB , Vol. 10, No. 6, pp. 719-724, Oct. 2003
10.3745/KIPSTB.2003.10.6.719,   PDF Download:

Abstract

This paper proposed a heuristic to enhance the speed of kNN without loss of its accuracy. The proposed heuristic minimizes the computation of the similarity between two documents which is the dominant factor in kNN. To do this, the paper proposes a method to calculate the upper limit of the similarity and to sort the training documents. The proposed heuristic was implemented on the existing framework of the text categorization, so called, AI::Categorizer and it was compared with the conventional kNN with the well-known data, Reuter-21578. The comparisons show that the proposed heuristic outperforms kNN about 30%~40% with respect to the execution time.


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Cite this article
[IEEE Style]
L. J. Mun, "An Improvement Of Efficiency For kNN By Using A Heuristic," The KIPS Transactions:PartB , vol. 10, no. 6, pp. 719-724, 2003. DOI: 10.3745/KIPSTB.2003.10.6.719.

[ACM Style]
Lee Jae Mun. 2003. An Improvement Of Efficiency For kNN By Using A Heuristic. The KIPS Transactions:PartB , 10, 6, (2003), 719-724. DOI: 10.3745/KIPSTB.2003.10.6.719.