Abstract In graph theory, the tree edit distance (TED) between two directed labeled and rooted trees is a popular research issue. As a combination optimization problem, calculating TED is widely used in the detection of the structural similarity of semi-structural documents. In this paper, a concept named tree semantic edit distance (TSED) with the corresponding formula is proposed. Then a distance measure based on both TED and TSED is presented. The proposed distance is applied in clustering the document object model (DOM) trees of extensible markup language (XML) documents. Experimental results show the proposed measure is better than those used TED only in terms of clustering precision and recall. The time complexity of the proposed algorithm is the same as those of algorithms for TED based on dynamic programming.
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2011, Vol. 24 
