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 eu convention on IR examine, ECIR 2012, held in Barcelona, Spain, in April 2012. The 37 complete papers, 28 poster papers and seven demonstrations provided during this quantity have been conscientiously reviewed and chosen from 167 submissions. The contributions are equipped in sections named: question illustration; blogs and online-community seek; semi-structured retrieval; overview; functions; retrieval types; picture and video retrieval; textual content and content material type, categorisation, clustering; structures potency; song; and posters.
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Extra resources for Advances in Information Retrieval: 34th European Conference on IR Research, ECIR 2012, Barcelona, Spain, April 1-5, 2012. Proceedings
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. 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.
Mining generalized query patterns from web logs. In: HICSS (2001) 12. : Wordnet: a lexical database for english. Communications of the ACM 38(11), 39–41 (1995) 13. : Constraint based frequent pattern mining for generalized query templates from web log. International Journal of Engineering, Science and Technology 2(11), 17–33 (2010) 14. : Improving recommendation for long-tail queries via templates. In: Proc. 20th International World Wide Web Conference, WWW 2011 (2011) Exploring Query Patterns in Email Search Morgan Harvey and David Elsweiler 1 Dept.
Finally, we describe our implementation of a lightweight prototype TUC identiﬁcation service that easily scales to support thousands of TUCs, and withstands high query loads with low latency. The rest of this paper is structured as follows. Section 2 surveys related work. Section 3 deﬁnes our metrics and optimization goals, whereas Section 4 describes the method for building the models. Section 5 presents the evaluation of our method across multiple transactional use cases. Section 6 overviews the TUC identiﬁcation service, and Section 7 concludes the paper.