|
ABSTRACT
Title |
: |
An Improved Algorithm for Text Document Clustering |
Authors |
: |
Latika |
Keywords |
: |
Document clustering, Improved k-means, Partitioning clustering, K-means, Feature selection, F-measure, VSM |
Issue Date |
: |
June 2015 |
Abstract |
: |
Due to the advancement of internet, the volume of the electronic documents available on the web is increasing day by day. Document clustering plays important role in organization and summarization of these documents. Thus, developing a fast and effective document clustering algorithm is of great importance. This paper presents an improved algorithm for document clustering. This algorithm is an enhancement of standard k-means algorithm. Experiments are conducted to evaluate the performance of improved algorithm and the results show that improved algorithm performs better than standard k-means algorithm. In this paper, feature selection is also applied to improve the clustering effectiveness. |
Page(s) |
: |
358-364 |
ISSN |
: |
2229-3345 |
Source |
: |
Vol. 6, Issue.6 |
|
|
|