An XQuery Specification for Requests with Preferences on XML Databases - Inria - Institut national de recherche en sciences et technologies du numérique
Communication Dans Un Congrès Année : 2020

An XQuery Specification for Requests with Preferences on XML Databases

Maurice Tchoupé Tchendji
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  • PersonId : 1132705
Patrik Joslin Kenfack
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Résumé

An exact query is a query in which the user specifies precisely what to retrieve from a database (XML or relational database). For these queries only data that strictly respect all user’s conditions is returned. XML documents are generally semi-structured. Due to the non-existence or lack of knowledge of the model of the document being queried, when exact queries are used, there is a high risk of obtaining an empty result (in the case of too specific queries) or too large (in the case of too vague queries). In contrast to exact queries, requests with preferences aim to return only the most relevant results in order to avoid empty or too important results as much as possible. To achieve this goal, requests with preferences generally consist of two parts: the first part is used to express strict constraints and the second part to express preferences or wishes. The satisfaction of both parts increases the relevance of the corresponding results. This paper presents XQuery preference, an extension of the XQuery language, that allows to express requests with preferences relating to both the values and the structure of an XML document. A representation model of such requests based on the Generalized Tree Pattern (GTP) model is also proposed in order to allow an evaluation of these requests through a tree pattern matching process. Integration of the proposed language in open source implementations of XQuery like BaseX, Berkeley DB XML, eXist-db, Galax and much more, will allow users to get much more relevant responses to their concerns.
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hal-03647265 , version 1 (20-04-2022)

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Maurice Tchoupé Tchendji, Patrik Joslin Kenfack. An XQuery Specification for Requests with Preferences on XML Databases. 16th IFIP International Conference on Open Source Systems (OSS), May 2020, Innopolis, Russia. pp.120-130, ⟨10.1007/978-3-030-47240-5_12⟩. ⟨hal-03647265⟩
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