By Norbert Fuhr, Mounia Lalmas, Saadia Malik, Gabriella Kazai
Content-oriented XML retrieval has been receiving expanding curiosity because of the common use of eXtensible Markup Language (XML), that is turning into a regular record structure on the internet, in electronic libraries,and publishing. by way of exploiting the enriched resource of syntactic and semantic details that XML markup offers, XML info retrieval (IR) platforms goal to enforce a extra centred retrieval approach and go back rfile elements, so-called XML components – rather than whole records – in keeping with a consumer question. This targeted retrieval strategy is of specific bene?t for collections containing lengthy files or files overlaying a large choice of themes (e.g., books, person manuals, felony files, etc.), the place clients’ e?ort to find correct content material will be decreased through directing them to the main correct elements of the files. imposing this, extra concentrated, retrieval paradigm implies that an XML IR approach wishes not just to ?nd proper details within the XML records, however it additionally has to figure out the suitable point of granularity to be again to the person. furthermore, the relevance of a retrieved part will be depending on assembly either content material and structural question conditions.
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Extra info 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
875. 75 6 1 2 2 (excluded) and 3 (included) of the ideal elements, then for 75 % of the users that means seeing 2 ideal elements with a precision 23 , and for 25 % of the users that means seeing 2 ideal elements with a precision 1. 75. The evaluations order the runs in an order which is appropriate: A has the maximum score and C is worse than D (D and C have their two first list item swapped, and D has a fully ideal element as its top ranked element). List B, containing only ideal elements, is overall better than C and D.
Eventually, we discuss the implication of the EPRUM user model for the notion of ideal lists and of overlap in Section 5. e. that it belongs to the “ideal recall base”). 2 The EPRUM Metric EPRUM is an extension of precision-recall: It is based on a definition whose special case is the standard precision-recall as defined in TREC . Precision is defined as the ratio of the minimum number of ranks that a user has to consult in the list returned by an ideal system and by the evaluated system, given that the user wants to see a given amount of ideal units.
Kazai, M. Lalmas, and N. 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.