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Recommendation of XML Documents exploiting Quality Metadata and Views

Laure Berti-Équille 1, 2
2 TEXMEX - Multimedia content-based indexing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : In this paper, we propose to query XML documents with a quality-based recommendation of the results. The document quality is modeled as a set of (criterion, value) pairs collected in metadata sets, and are associated with the indexed XML documents. We implemented four basic operations to achieve quality recommendation: 1) annotation with metadata describing the documents quality, 2) indexing the documents, 3) matching queries and quality requirements , and 4) viewing the recommended parts of the documents. The quality requirements of each user are kept as individual quality profiles (called XPS files). Every XML document in the document database refers to a quality style sheets (called XQS files) which allow the specification of several matching strategies with rules that associate parts (sub-trees) of XML documents to user profile quality requirements. An algorithm is described for evaluation of the quality style sheets and user profiles in order to build an "adaptive quality view" of the retrieved XML document. The paper describes the general architecture of our quality-based recommender system for XML documents.
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Submitted on : Friday, August 10, 2018 - 4:54:18 PM
Last modification on : Wednesday, August 5, 2020 - 3:46:26 AM
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  • HAL Id : hal-01856346, version 1


Laure Berti-Équille. Recommendation of XML Documents exploiting Quality Metadata and Views. 2nd Intl. Workshop on Data and Information Quality (DIQ 2005) in conjunction with the 17th Conference on Advanced Information Systems Engineering (CAiSE’05), Jun 2005, Porto, Portugal. pp.1-15. ⟨hal-01856346⟩



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