By Norbert Fuhr, Mounia Lalmas, Saadia Malik, Gabriella Kazai
Content-oriented XML retrieval has been receiving expanding curiosity as a result of common use of eXtensible Markup Language (XML), that is changing into a customary rfile 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 target to enforce a extra centred retrieval procedure and go back rfile elements, so-called XML parts – rather than whole records – in accordance with a consumer question. This targeted retrieval method is of specific bene?t for collections containing lengthy records or records overlaying a large choice of issues (e.g., books, person manuals, criminal files, etc.), the place clients’ e?ort to find suitable content material should be decreased by way of directing them to the main correct elements of the files. enforcing this, extra centred, retrieval paradigm signifies that an XML IR procedure wishes not just to ?nd suitable info within the XML files, however it additionally has to figure out the suitable point of granularity to be lower back to the person. moreover, the relevance of a retrieved part could 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
43–57, 2006. c Springer-Verlag Berlin Heidelberg 2006 44 J. A. " size="30" rsize="30"/> Fig. 1. A sample from the INEX 2005 CO topic 203 relevance judgements for article co/2000/r7108. , 1 and 2), size denotes the element size (measured as total number of contained characters), while rsize shows the actual number of characters highlighted as relevant by the assessor judgements obtained for INEX 2005 Content Only (CO) topic 203. For each judged element, E shows the exhaustivity of the element, with possible values of ?
1. Calculation of nxCG and eﬀort-precision (ep) 22 G. Kazai and M. Lalmas xCG[i] gr[i] := = xCI[n] i j=1 xG[j] n j=1 xI[j] (12) where n is the total number of documents in the recall-base. The meaning of eﬀort-precision at a given gain-recall value is the amount of relative eﬀort (where eﬀort is measured in terms of number of visited ranks) that the user is required to spend when scanning a system’s output ranking compared to the eﬀort an ideal ranking would take in order to reach a given level of gain relative to the total gain that can be obtained.
Before the ﬁnal gain value can be assigned to xG[i], we apply a dependency normalisation function, which ensures that the total score for any sub-tree of an ideal node cannot exceed the maximum score achievable when the ideal node itself is retrieved. For example, an ideal node may have a large number of relevant child nodes whose total RV score may exceed that of the ideal node. The following dependency normalisation function, rvnorm , safeguards against this by ensuring that for any S cj ∈ S, rv(ci ) + rv(cj ) ≤ rv(cideal ) holds: S rvnorm (ci ) = min(rv(ci ), rv(cideal ) − rv(cj )) (8) where cideal is the ideal node that is on the same relevant path as ci , S is the set of nodes in the ideal node’s sub-tree that have already been retrieved (before ci ).