Many modern applications produce and process XML data, which is queried in its both structural and textual component. This is especially useful if we consider a casual user who looks for information in web-based database systems or intranets containing XML data, like online shops, airline reservations, digital libraries catalogues or any other, and does not expect an exact answer. Many websites are built from document-centric XML documents [3]. A remarkable characteristic of such XML data collections is that they are mostly heterogeneous, i.e. they contain domainfocused data, possibly valid w.r.t. various DTDs or XML schemes. XML documents can come from various sources. These collections can be managed as XML databases [5] as well as collections, providing an approximate way for users to search their contents. To ensure such functionality, it is required to approach these collections with both database and information retrieval (IR) methods. Current XML query languages like XPath and XQuery are applicable rather for data-centric than for document-centric XML data. Moreover, XML schemes are often necessary for their use. In other words, the languages are not longer appropriate for searching in such environments because they can not cope with the diversity of data. Hence, a research of integration of database querying and IR in context of XML is undoubtedly interesting and promising trend. Despite of the fact that a variety of systems that support such methods have been proposed, conventional IR techniques [2], e.g. vector space model, can be employed only restrictedly. The reason for it is that two types of queries should be dealt with: content-only (CO) queries, i.e. the traditional ones in IR, and content-and-structure (CAS) queries. A number of techniques to extend the vector space model have been designed, e.g. [6], [7], [8], [9], [11], and [12]. A usual critique of the mentioned approaches is that they not sufficiently reflect the structure of XML documents. A more advanced, twophase evaluation schema is proposed in [1]. First, a modified vector space model is employed to obtain similarity scores for the textual nodes of XML trees. Then, the scores are propagated upward in the XML-trees with a possible modification and possibly new scores of other nodes are generated. In [13] we described a matrix model based on an extension of the vector space model for XML data. A document D in a collection of XML documents C is represented by a matrix D, whose each row vector wt associated with a term t contains the weights of t for each path occurring in C. A query Q considered also as an XML tree is expressed as a matrix Q. The matrix model proposes to evaluate the degree of similarity of D with regard to the Q as the correlation between the matrices D and Q.
Experiments have shown that it is not possible to rely only on this score. Instead we
adjust the matrix D by an additional data structure, so called a path transform matrix,
which reflects relationships among paths. The same is done for the matrix Q. Then,
the resulted transformed matrices TD and TQ are used for query processing. First
experiments have been done with the well-known collection of Shakespeare’s plays
[
In next development of the matrix model we found its critical points and proposed
its new version based on the approach [