By Norbert Fuhr, Mounia Lalmas, Saadia Malik, Gabriella Kazai
Content-oriented XML retrieval has been receiving expanding curiosity as a result of the frequent use of eXtensible Markup Language (XML), that's turning into a customary rfile layout on the internet, in electronic libraries,and publishing. by way of exploiting the enriched resource of syntactic and semantic info that XML markup offers, XML details retrieval (IR) platforms objective to enforce a extra centred retrieval approach and go back record elements, so-called XML parts – rather than entire files – in accordance with a person question. This targeted retrieval procedure is of specific bene?t for collections containing lengthy files or records overlaying a wide selection of issues (e.g., books, person manuals, criminal files, etc.), the place clients’ e?ort to find appropriate content material may be decreased via directing them to the main proper components of the files. enforcing this, extra targeted, retrieval paradigm implies that an XML IR procedure wishes not just to ?nd suitable details within the XML files, however it additionally has to figure out the precise point of granularity to be again to the person. additionally, the relevance of a retrieved part might 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
Table 1. 85 Correlation of Quantisation Functions Next, we examined correlation among the diﬀerent quantisation functions by calculating the Kendall τ correlation between the resulting respective system rankings. Thorough, SSCAS, SVCAS, VSCAS, VVCAS. This means that the average correlation for each measure was calculated over 80 correlation scores: 8 tasks, each having each having results reported for ten measures. Although diﬀerent tasks and diﬀerent measures resulted in somewhat diﬀerent correlation values amongst the diﬀerent quantisation functions, the overall general trend is reﬂected within this table.
Table 4. Precision-recall for the list A-D (Fetch&Browse). The precision for the four lists and four recall intervals are shown. The line “correspondence” shows what is the number of ideal elements the user wants to see if, among the elements in the ideal set, (1) he considers that only elements with an exhaustivity 2 are ideal (2) he considers that elements with an exhaustivity at least 1 are ideal. 49 The evaluations are as expected; list A has the maximum score, followed by list B (where the two documents were swapped).
3. N. Kando, K. Kuriyama, and M. Yoshioka. Information retrieval system evaluation using multi-grade relevance judgements - discussion on averageable single-numbered measures (in japanese). Technical report, 2001. INEX 2005 Evaluation Measures 29 4. G. Kazai and M. Lalmas. eXtended Cumulated Gain Measures for the Evaluation of Content-oriented XML Retrieval. ACM Transactions on Information Systems (ACM TOIS), To appear. 5. J. Kek¨ al¨ ainen and K. J¨ arvelin. Using graded relevance assessments in IR evaluation.