Albakour, M-Dyaa; Nanas, Nikolaos; Kruschwitz, Udo; Fasli, Maria; Kim, Yunhyong; Song, Dawei and De Roeck, Anne
(2011).
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| URL: | http://www.springerlink.com/content/w0978015n1622h... |
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| DOI (Digital Object Identifier) Link: | http://dx.doi.org/doi:10.1007/978-3-642-20161-5_60 |
| Google Scholar: | Look up in Google Scholar |
Abstract
User evaluations of search engines are expensive and not easy to replicate. The problem is even more pronounced when assessing adaptive search systems, for example system-generated query modification suggestions that can be derived from past user interactions with a search engine. Automatically predicting the performance of different modification suggestion models before getting the users involved is therefore highly desirable. AutoEval is an evaluation methodology that assesses the quality of query modifications generated by a model using the query logs of past user interactions with the system. We present experimental results of applying this methodology to different adaptive algorithms which suggest that the predicted quality of different algorithms is in line with user assessments. This makes AutoEval a suitable evaluation framework for adaptive interactive search engines.
| Item Type: | Conference Item |
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| Copyright Holders: | 2011 Springer-Verlag |
| Extra Information: | Advances in Information Retrieval
33rd European Conference on IR Research, ECIR 2011 Dublin, Ireland, April 18-21, 2011 Proceedings edited by Paul Clough, Colum Foley, Cathal Gurrin, Gareth J.F. Jones, Wessel Kraaij, Hyowon Lee, Vanessa Murdoch Berlin : Springer-Verlag, 2011 Lecture Notes in Computer Science, 6611 ISBN 978-3-642-20160-8 pp. 605-610 |
| Academic Unit/Department: | Mathematics, Computing and Technology > Computing Mathematics, Computing and Technology |
| Interdisciplinary Research Centre: | Centre for Research in Computing (CRC) |
| Related URLs: | |
| Item ID: | 34686 |
| Depositing User: | Dawei Song |
| Date Deposited: | 18 Oct 2012 11:04 |
| Last Modified: | 24 Oct 2012 11:24 |
| URI: | http://oro.open.ac.uk/id/eprint/34686 |
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