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12 · Alsayed Algergawy et al.
Fig. 6: Similarity measures.
both features should be taken into account. An extended version of the vector space
model called structural link vector model (SLVM) is used to capture syntactic structure
tagged by XML elements [Yang et al. 2009]. SLVM represents an XML document doc x
using a document feature matrix ∆ x ∈ R n×m , given as
∆ x = [∆ x(1) , ∆ x(2) , ..., ∆ x(m) ]
where m is the number of distinct XML elements, ∆ x(i) ∈ R n is the TFIDF feature
vector representing the ith XML element, (1 ≤ i ≤ m), given as ∆ x(i) =
TF(ρ j , doc x .e i ).IDF(ρ j ) for all j = 1 to n, where TF(ρ j , doc x .e i ) is the frequency
of the term w j in the element e i of doc x . The SLVM representation of an XML document
instance for D1 depicted in Fig. 1a is reported in Fig. 5b, which illustrates, for
example, that the term XML appears one time in D1 (from the document feature vector
d x ) under the element title (from the document feature matrix ∆ x ).
Another vector-based representation that captures both structure and content of the XML
data is represented in [Yoon et al. 2001]. The bitmap indexing technique, shown in Fig.
5d is extended, where a set of XML documents is represented using a 3-dimensional
matrix, called BitCube. Each document is defined as a set of (path, word), where path
is a root-to-leaf path, and word denotes the word or content of the path. If a document
has path, then the corresponding bit in the bitmap index is set to 1. Otherwise, all bits
are set to 0 (and if path contains a word, the bit is set to 1, and 0 otherwise).
4. SIMILARITY MEASURES AND COMPUTATION
Starting from the representation model of objects and their features, the similarity between
XML data can be identified and determined by exploiting objects, objects’ features, and
relationships among them. There are various aspects that allow the description and categorization
of XML data similarity measures, such as the kind of methodology being used, the
kind of XML data representation, and the planned application domain [Tekli et al. 2009].
In the following, for homogeneity of presentation, we survey several XML similarity measures
based on the used data representation, as shown in Fig. 6.
ACM Computing Surveys, Vol. , No. , 2009.