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 booklet constitutes the complaints of the thirty fourth ecu 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 equipped in sections named: question illustration; blogs and online-community seek; semi-structured retrieval; overview; purposes; retrieval types; snapshot and video retrieval; textual content and content material type, categorisation, clustering; platforms potency; tune; 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
An example from the News logs of a removal that made the results more specific is the following. A searcher first used the query cleaner of the year. 5). The user then modified the query into cleaner, apparently to remove the irrelevant year results. This behavior is consistent with the union-based interpretation: searchers remove terms B from a query ‘A B’ to get rid of irrelevant results that are only about B. A similar removal example taken from the web 20k logs transforms shoulder pain erand numbness in index finger to numbness in index finger.
This would explain clicks on diﬀerent pages. In email searches, on the other hand, the user usually has a speciﬁc email in mind that he believes will solve his need . Thus, it makes sense that this behaviour is not visible in our data. Figure 3 also shows a clear temporal aspect to information needs. 4855). If you take high message overlap to be an indicator of reﬁnding intent, this suggests that the information need associated with a query changes with time. This pattern contrasts sharply with the ﬁndings reported for web search where a repeated query has at least 90% probability of a repeat click when it is repeated up to 30 days after the previous submission .
More recent work has looked at querying behaviour over signiﬁcantly longer time periods; examining temporal aspects such as query repetition and how pages are re-found [13,15,16,3]. These analyses reveal that query re-use behaviour is extremely common. For example 33% of all SE queries submitted have been identically submitted previously by the same user and for 39% of all queries the user returns to a Web page that he has found before via a separate search . SE log analysis has shown that queries submitted with the intention of re-ﬁnding are typically shorter than those for new content and the clicked on pages for such queries tend to rank higher in the results list .