Author(s)

Maurice Tchoupé Tchendji¹, Lionel Tadonfouet², Thomas Tébougang Tchendji¹

¹Department of Mathematics and Computer Science, Faculty of Sciences, University of Dschang, Dschang, Cameroon.
²INRIA, Paris, France.

In the XML community, exact queries allow users to specify exactly what they want to check and/or retrieve in an XML document. When they are applied to a semi-structured document or to a document with an overly complex model, the lack or the ignorance of the explicit document model (DTD—Document Type Definition, Schema, etc.) increases the risk of obtaining an empty result set when the query is too specific, or, too large result set when it is too vague (e.g. it contains wildcards such as “*”). The reason is that in both cases, users write queries according to the document model they have in mind; this can be very far from the one that can actually be extracted from the document. Opposed to exact queries, preference queries are more flexible and can be relaxed to expand the search space during their evaluations. Indeed, during their evaluation, certain constraints (the preferences they contain) can be relaxed if necessary to avoid precisely empty results; moreover, the returned answers can be filtered to retain only the best ones. This paper presents an algorithm for evaluating such queries inspired by the TreeMatch algorithm proposed by Yao et al. for exact queries. In the proposed algorithm, the best answers are obtained by using an adaptation of the Skyline operator (defined in relational databases) in the context of documents (trees) to incrementally filter into the partial solutions set, those which satisfy the maximum of preferential constraints. The only restriction imposed on documents is No-Self-Containment.

Semi-Structured Documents, Preference Queries, Tree Pattern Matching, TreeMatch Algorithm, XML, The Skyline Operator

Tchendji, M. , Tadonfouet, L. and Tchendji, T. (2019) A Tree Pattern Matching Algorithm for XML Queries with Structural Preferences. Journal of Computer and Communications, 7, 61-83. doi: 10.4236/jcc.2019.71006.