@inproceedings{bd328172fdf647b681cc4ce0a97e8f7e,
title = "KNN text categorization algorithm based on semantic centre",
abstract = "As a classical statistical pattern recognition algorithm characterized with high accuracy and stability, KNN has been used widely in text categorization. But since KNN's time complexity is directly proportional to the sample size, its classification speed is very slow. In this paper, we propose a new KNN text categorization algorithm based on semantic centre, which we call SKNN, to speed up the classification. The basic thread is to replace the large number of original sample documents with a small amount of sample semantic centers. Experiments have proved that the SKNN's clarification is over 10 times as fast as that of the traditional KNN and its F1 value is approximately equal to SVM and traditional KNN algorithm.",
keywords = "KNN, Semantic center, Text categorization",
author = "Zhang, {Xiao Fei} and Huang, {He Yan} and Zhang, {Ke Liang}",
year = "2009",
doi = "10.1109/ITCS.2009.57",
language = "English",
isbn = "9780769536880",
series = "Proceedings - 2009 International Conference on Information Technology and Computer Science, ITCS 2009",
pages = "249--252",
booktitle = "Proceedings - 2009 International Conference on Information Technology and Computer Science, ITCS 2009",
note = "2009 International Conference on Information Technology and Computer Science, ITCS 2009 ; Conference date: 25-07-2009 Through 26-07-2009",
}