By Nicholas J. Belkin (auth.), Craig Macdonald, Iadh Ounis, Vassilis Plachouras, Ian Ruthven, Ryen W. White (eds.)
This ebook constitutes the refereed complaints of the thirtieth annual eu convention on details Retrieval learn, ECIR 2008, held in Glasgow, united kingdom, in March/April 2008.
The 33 revised complete papers and 19 revised brief papers provided including the abstracts of three invited lectures and 32 poster papers have been rigorously reviewed and chosen from 139 complete article submissions. The papers are geared up in topical sections on evaluate, net IR, social media, cross-lingual details retrieval, idea, video, illustration, wikipedia and e-books, in addition to specialist search.
Read Online or Download Advances in Information Retrieval: 30th European Conference on IR Research, ECIR 2008, Glasgow, UK, March 30-April 3, 2008. Proceedings PDF
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Additional info for Advances in Information Retrieval: 30th European Conference on IR Research, ECIR 2008, Glasgow, UK, March 30-April 3, 2008. Proceedings
We call this “precision of preferences” or ppref for short. More formally, over all pairs of pages i, j such that i is preferred to j by an assessor, ppref is the proportion for which the engine ranked i above j. If neither i nor j is ranked, ppref ignores the pair. If i is ranked but j is not, ppref considers i to have been ranked above j. The pairs in ppref can be weighted for a measure we call wpref. We use a rank-based weighting scheme: for pages at ranks i and j such that j > i, let 1 . wpref is then the sum of weights wij over pairs i, j the weight wij = log (j+1) 2 such that i is preferred to j and the rank of i is less than the rank of j.
They also show that by using a whole range of implicit user feedback such as page dwell time, the precision of rankings can be increased signiﬁcantly. Evaluation Metrics. Experimental work in information retrieval typically follows the “Cranﬁeld” paradigm, where a search system is evaluated by running a set of queries over a ﬁxed collection. A human judge assesses the relevance of each document for each query and, based on the position of relevant documents in the result list, a variety of performance metrics can be calculated.
12 K. Järvelin et al. Concatenated Top-10 Results: Average sDCG in Scenario D 60,00 50,00 40,00 sDCG S-1-T-10 S-1-T-10/4Q 30,00 S-2-T-10 S-2-T-10/4Q 20,00 10,00 0,00 0 10 20 30 40 50 60 Session Rank Fig. 3. Session performance by concatenated Top-10 results averaged across all sessions of Scenario D in Systems 1 (S-1-T-10) and 2 (S-2-T-10) and across the sessions that constructed at least four queries (S-1-T-10/4Q and S-2-T-10/4Q) (b=2; bq=4) sDCG in Individual Sessions, Top-10, System 1 120,00 100,00 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 sDCG 80,00 60,00 40,00 20,00 0,00 0 10 20 30 40 50 60 Concatenated Session Rank Fig.