TY - JFULL
AU - Matthias Dehmer and Frank Emmert Streib and Alexander Mehler and Jürgen Kilian
PY - 2007/11/
TI - Measuring the Structural Similarity of Web-based Documents: A Novel Approach
T2 - International Journal of Computer and Information Engineering
SP - 3069
EP - 3076
VL - 1
SN - 1307-6892
UR - https://publications.waset.org/pdf/15928
PU - World Academy of Science, Engineering and Technology
NX - Open Science Index 10, 2007
N2 - 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 DOM-Trees. 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 web-based documents represented by so called generalized trees which are more general than DOM-Trees which represent only directed rooted trees.We will design a new similarity measure for graphs representing web-based 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 web-based documents.
ER -