Score Region Algebra: A Framework for Structured IR

V. Mihajlovic

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Abstract

We address the problem of developing a flexible framework for information retrieval (IR) in structured documents, such as XML. The framework is able to support a wide range of structured IR queries, transparent instantiations of different retrieval models, and different physical implementations. It is based on so-called score region algebra (SRA) that can express the following four essential ranked retrieval aspects for structured IR: term and element selection, element relevance score computation, element score propagation, and element score combination. Our preliminary research shows that different instantiations of each aspect, as well as different combinations of these instantiations, yield significantly different results. Our goal is to better understand structured IR by studying these aspects alone and their combination in the framework of SRA, and to use this knowledge to improve our structured IR system.
Original languageEnglish
Title of host publicationSIGIR 2005
Subtitle of host publicationProceedings of Twenty-Eighth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
Place of PublicationNew York, NY
PublisherACM Press
Pages685
Number of pages5
ISBN (Print)1-59593-034-5
DOIs
Publication statusPublished - 15 Aug 2005
Event28th Annual International ACM/SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2005 - Salvador, Brazil
Duration: 15 Aug 200519 Aug 2005
Conference number: 28

Conference

Conference28th Annual International ACM/SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2005
Abbreviated titleSIGIR
CountryBrazil
CitySalvador
Period15/08/0519/08/05

Keywords

  • EWI-7661
  • IR-53293
  • DB-XMLIR: XML INFORMATION RETRIEVAL
  • METIS-225854

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    Mihajlovic, V. (2005). Score Region Algebra: A Framework for Structured IR. In SIGIR 2005: Proceedings of Twenty-Eighth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 685). New York, NY: ACM Press. https://doi.org/10.1145/1076034.1230135