By Vera Hollink, Jiyin He, Arjen de Vries (auth.), Ricardo Baeza-Yates, Arjen P. de Vries, Hugo Zaragoza, B. Barla Cambazoglu, Vanessa Murdock, Ronny Lempel, Fabrizio Silvestri (eds.)
This publication constitutes the court cases of the thirty fourth ecu convention on IR learn, ECIR 2012, held in Barcelona, Spain, in April 2012. The 37 complete papers, 28 poster papers and seven demonstrations offered during this quantity have been conscientiously reviewed and chosen from 167 submissions. The contributions are prepared in sections named: question illustration; blogs and online-community seek; semi-structured retrieval; review; purposes; retrieval types; photograph and video retrieval; textual content and content material type, categorisation, clustering; structures potency; song; and posters.
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Additional resources for Advances in Information Retrieval: 34th European Conference on IR Research, ECIR 2012, Barcelona, Spain, April 1-5, 2012. Proceedings
59% (58+333 / 665) of equal query pairs had overlap while 49% (82+313 / 802) of diﬀerent query pairs had some overlapping messages. The small diﬀerence between these ﬁgures could be an artefact of the way people search for emails and the properties of email collections themselves. e. the number of messages clicked per query is much larger. 17 message clicks compared to the 1 or less page clicks associated with SE queries . Secondly, email collections are of course much smaller than the web, which naturally increases the chance of serendipitous overlap.
New movie releases for online rental). In general, template-based models improve the recall achieved by whitelists by about 20%. From the model size perspective, the compressed template models are consistently smaller than the respective whitelists. However, even the compressed model sizes range from hundreds to tens of thousands of templates. Therefore, it is virtually impossible to anticipate (and manually craft) query patterns for a speciﬁc use case, especially if high recall levels are desired.
3 Overlapping Clicks with Diﬀerent Queries A ﬁnal situation of interest in Table 2 is when there was overlap in clicks, but the queries were not the same (cells 4 and 5). Examining these queries however, reveals that although the queries were not the same, often they were very similar. Examples of query pairs for chains where message overlap is high (overlap coeﬃcient >75% 4 ), but queries do not match include:“mar”/“maria”, “jen”/“jennifer”, “virt”/“virtual”, “lisa”/“lisa nathan”, “johnston”/“david joh”5 .