FICW: frequent itemset based text clustering with window constraint Most of the existing text clustering algorithms overlook the fact that a document is a word sequence with semantic information. There is some important semantic information existing in the positions of words in the sequence. In this paper, a novel method named Frequent Itemset-based Clustering with Window (FICW) is proposed which makes use of the semantic information for text clustering with a window constraint. The experimental results obtained from tests on three (hypertext) text sets show that FICW outperforms the method compared in both clustering accuracy and efficiency.
References in zbMATH (referenced in 1 article , 1 standard article )
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- Zhou, Chong; Lu, Yansheng; Zou, Lei; Hu, Rong: FICW: frequent itemset based text clustering with window constraint (2006)