Incremental clustering algorithm based on phrase-semantic similarity histogram

Incremental document clustering is an important key in organizing, searching, and browsing large datasets. Although, many incremental document clustering methods have been proposed, they do not focus on linguistic and semantic properties of the text Incremental clustering algorithms are preferred to traditional clustering techniques with the advent of online publishing in the World Wide Web. In this paper, an incremental document clustering algorithm is introduced. The proposed algorithm integrates the text semantic to the incremental clustering process. The clusters are represented using semantic histogram which measures the distribution of semantic similarities within each cluster. Experimental results show that the proposed algorithm has a promising clustering performance compared to standard clustering methods.