Overview of the second text retrieval conference (TREC-2)
TREC-2 Proceedings of the second conference on Text retrieval conference
Expressiveness of concept expressions in first-order description logics
Artificial Intelligence
A Web Odyssey: from Codd to XML
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Modal logic
Accelerating XPath location steps
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Structural Properties of XPath Fragments
ICDT '03 Proceedings of the 9th International Conference on Database Theory
Processing content-oriented XPath queries
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Finding an application-appropriate model for XML data warehouses
Information Systems
Ontology-DTD matching algorithm for efficient XML query
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
INEX'04 Proceedings of the Third international conference on Initiative for the Evaluation of XML Retrieval
Competitive intelligence for SMEs: a web-based decision support system
International Journal of Business Information Systems
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On the Web, there is a pervasive use of XML to give lightweight semantics to textual collections. Such document-centric XML collections require a query language that can gracefully handle structural constraints as well as constraints on the free text of the documents. Our main contributions are three-fold. First, we outline two fragments of XPath tailored to users that have varying degrees of understanding of the XML structure used, and give both syntactic and semantic characterizations of these fragments. Second, we extend XPath with an about function having a best-match semantics based on the relevance of the document component for the expressed information need. Third, we evaluate the resulting query language using the INEX 2003 test suite, and show that best-match approaches outperform exact-match approaches for evaluating content-and-structure queries.