Matthias Dehmer and Frank Emmert Streib and Alexander Mehler and Jürgen Kilian
Measuring the Structural Similarity of Webbased Documents A Novel Approach
3070 - 3076
2007
1
10
International Journal of Computer and Information Engineering
https://publications.waset.org/pdf/15928
https://publications.waset.org/vol/10
World Academy of Science, Engineering and Technology
Most known methods for measuring the structural similarity of document structures are based on, e.g., tag measures, path metrics and tree measures in terms of their DOMTrees. Other methods measures the similarity in the framework of the well known vector space model. In contrast to these we present a new approach to measuring the structural similarity of webbased documents represented by so called generalized trees which are more general than DOMTrees which represent only directed rooted trees.We will design a new similarity measure for graphs representing webbased hypertext structures. Our similarity measure is mainly based on a novel representation of a graph as strings of linear integers, whose components represent structural properties of the graph. The similarity of two graphs is then defined as the optimal alignment of the underlying property strings. In this paper we apply the well known technique of sequence alignments to solve a novel and challenging problem Measuring the structural similarity of generalized trees. More precisely, we first transform our graphs considered as high dimensional objects in linear structures. Then we derive similarity values from the alignments of the property strings in order to measure the structural similarity of generalized trees. Hence, we transform a graph similarity problem to a string similarity problem. We demonstrate that our similarity measure captures important structural information by applying it to two different test sets consisting of graphs representing webbased documents.
Open Science Index 10, 2007