Inverted Index based Modified Version of K-Means Algorithm for Text Clustering


Taeho Jo, Journal of Information Processing Systems Vol. 4, No. 2, pp. 67-76, Apr. 2008

10.3745/JIPS.2008.4.2.067
Keywords: String Vector, K Means Algorithm, Text Clustering
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Abstract

This research proposes a new strategy where documents are encoded into string vectors and modified version of k means algorithm to be adaptable to string vectors for text clustering. Traditionally, when k means algorithm is used for pattern classification, raw data should be encoded into numerical vectors. This encoding may be difficult, depending on a given application area of pattern classification. For example, in text clustering, encoding full texts given as raw data into numerical vectors leads to two main problems: huge dimensionality and sparse distribution. In this research, we encode full texts into string vectors, and modify the k means algorithm adaptable to string vectors for text clustering.


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Cite this article
[APA Style]
Taeho Jo (2008). Inverted Index based Modified Version of K-Means Algorithm for Text Clustering. Journal of Information Processing Systems, 4(2), 67-76. DOI: 10.3745/JIPS.2008.4.2.067.

[IEEE Style]
T. Jo, "Inverted Index based Modified Version of K-Means Algorithm for Text Clustering," Journal of Information Processing Systems, vol. 4, no. 2, pp. 67-76, 2008. DOI: 10.3745/JIPS.2008.4.2.067.

[ACM Style]
Taeho Jo. 2008. Inverted Index based Modified Version of K-Means Algorithm for Text Clustering. Journal of Information Processing Systems, 4, 2, (2008), 67-76. DOI: 10.3745/JIPS.2008.4.2.067.