By Norbert Fuhr, Mounia Lalmas, Saadia Malik, Gabriella Kazai
Content-oriented XML retrieval has been receiving expanding curiosity as a result of frequent use of eXtensible Markup Language (XML), that's changing into a customary rfile structure on the internet, in electronic libraries,and publishing. by means of exploiting the enriched resource of syntactic and semantic info that XML markup presents, XML info retrieval (IR) platforms goal to enforce a extra concentrated retrieval method and go back rfile parts, so-called XML parts – rather than whole records – according to a person question. This centred retrieval technique is of specific bene?t for collections containing lengthy records or files masking a wide selection of issues (e.g., books, consumer manuals, felony records, etc.), the place clients’ e?ort to find suitable content material might be diminished by way of directing them to the main suitable elements of the files. enforcing this, extra targeted, retrieval paradigm signifies that an XML IR approach wishes not just to ?nd suitable info within the XML files, however it additionally has to figure out the precise point of granularity to be lower back to the person. additionally, the relevance of a retrieved part should be depending on assembly either content material and structural question conditions.
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Extra resources for Advances in XML Information Retrieval and Evaluation: 4th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2005, Dagstuhl Castle, Germany, November 28-30, 2005. Revised Selected Papers
List B, containing only ideal elements, is overall better than C and D. 38 B. Piwowarski Table 1. Evolution of the different probabilities, with respect to the different lists (A, B, C, D) for the Focussed/VVCAS/SVCAS tasks. The three columns below probability P(x ∈ Si ) correspond respectively to the probability that element a, b, or c is seen by the user after rank i. The probability P2 (resp. P1 ) is the probability that the user found at least ... ideal elements after rank i, given that he is only satisfied with elements at least highly (resp.
Fuhr. Overview of inex 2005. In N. Fuhr, M. Lalmas, S. Malik, and G. Kazai, editors, Advances in XML Information Retrieval and Evaluation: Fourth Workshop of the INitiative for the Evaluation of XML Retrieval (INEX 2005), Schloss Dagstuhl, 28-30 November 2005, volume 3977 of Lecture Notes in Computer Science, pages 1–15. Springer-Verlag, 2006. 7. C. J. V. Rijsbergen. Information Retrieval. Butterworth-Heinemann, Newton, MA, USA, 1979. html. 8. T. Sakai. New performance metrics based on multigrade relevance: Their application to question answering.
ACM Press.  G. Kazai and M. Lalmas. Notes on what to measure in inex. In A. Trotman, M. Lalmas, and N. Fuhr, editors, Proceedings of the INEX 2005 Workshop on Element Retrieval Methodology. University of Otago, Univerisity of Glasgow, Information Retrieval Festival, 2005.  B. Piwowarski and P. Gallinari. Expected ratio of relevant units: A measure for structured information retrieval. In N. Fuhr, M. Lalmas, and S. Malik, editors, INitiative for the Evaluation of XML Retrieval (INEX). Proceedings of the Second INEX Workshop, Dagstuhl, France, Dec.