Advances in Information Retrieval: 34th European Conference by Vera Hollink, Jiyin He, Arjen de Vries (auth.), Ricardo
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 ebook constitutes the complaints of the thirty fourth eu convention on IR examine, ECIR 2012, held in Barcelona, Spain, in April 2012. The 37 complete papers, 28 poster papers and seven demonstrations awarded during this quantity have been rigorously reviewed and chosen from 167 submissions. The contributions are prepared in sections named: question illustration; blogs and online-community seek; semi-structured retrieval; assessment; purposes; retrieval types; picture and video retrieval; textual content and content material type, categorisation, clustering; structures potency; music; and posters.
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Additional info for Advances in Information Retrieval: 34th European Conference on IR Research, ECIR 2012, Barcelona, Spain, April 1-5, 2012. Proceedings
The next section describes our heuristic solution. 4 Model Construction The model training process, depicted in Figure 3, runs on a large query log sample. It accepts as plug-ins a target page classiﬁer that identiﬁes the pages associated with a particular use-case’s service(s), and a query templatizer that produces the candidate templates for queries. The page classiﬁer may be as simple as a URL preﬁx validator, when target pages share a common preﬁx, or some more complex content-based ﬁlter. g.
Therefore, it is virtually impossible to anticipate (and manually craft) query patterns for a speciﬁc use case, especially if high recall levels are desired. Note that in contrast to whitelists, template model sizes do not necessarily grow with the increase in recall (despite spanning more queries). The reason is that as recall increases, more general templates (that often exhibit lower CTR) are included in the model, thereby causing more speciﬁc templates to become redundant. Hence, as recall increases, the inclusion of general templates may produce more compact models.
10] address predicting the transactional nature of a Web document. The approaches discussed above rely on the retrieved set of documents for a given query and on users’ search behavior. This not only raises performance concerns when tested in real-time, as acknowledged in , but also limits the practical value of the proposed methods. Our approach is eﬃcient in terms of online performance since its runtime component only depends on simple dictionary look-ups on the query itself. 3 Problem Definition and Metrics Given a transactional use-case, the template selection problem can be formalized as follows.