%0 Book Section %1 citeulike:3428483 %A McCarthy, Kevin %A McGinty, Lorraine %A Smyth, Barry %B Case-Based Reasoning Research and Development %C Berlin, Heidelberg %D 2007 %E Weber, Rosina O. %E Richter, Michael M. %I Springer Berlin Heidelberg %J Case-Based Reasoning Research and Development %K group-recommendation %P 299--313 %R 10.1007/978-3-540-74141-1_21 %T Case-Based Group Recommendation: Compromising for Success %U http://dx.doi.org/10.1007/978-3-540-74141-1_21 %V 4626 %X There are increasingly many recommendation scenarios where recommendations must be made to satisfy groups of people rather than individuals. This represents a significant challenge for current recommender systems because they must now cope with the potentially conflicting preferences of multiple users when selecting items for recommendation. In this paper we focus on how individual user models can be aggregated to produce a group model for the purpose of biasing recommendations in a critiquing-based, case-based recommender. We describe and evaluate 3 different aggregation policies and highlight the benefits of group recommendation using live-user preference data. %& 21 %@ 978-3-540-74138-1

@incollection{citeulike:3428483, abstract = {{There are increasingly many recommendation scenarios where recommendations must be made to satisfy groups of people rather than individuals. This represents a significant challenge for current recommender systems because they must now cope with the potentially conflicting preferences of multiple users when selecting items for recommendation. In this paper we focus on how individual user models can be aggregated to produce a group model for the purpose of biasing recommendations in a critiquing-based, case-based recommender. We describe and evaluate 3 different aggregation policies and highlight the benefits of group recommendation using live-user preference data.}}, added-at = {2018-03-19T12:24:51.000+0100}, address = {Berlin, Heidelberg}, author = {McCarthy, Kevin and McGinty, Lorraine and Smyth, Barry}, biburl = {https://www.bibsonomy.org/bibtex/27622cb7b536f9a556797b25917407c3b/aho}, booktitle = {Case-Based Reasoning Research and Development }, chapter = 21, citeulike-article-id = {3428483}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1421130.1421153}, citeulike-linkout-1 = {http://dx.doi.org/10.1007/978-3-540-74141-1_21}, citeulike-linkout-2 = {http://www.springerlink.com/content/c452l46758002741}, doi = {10.1007/978-3-540-74141-1_21}, editor = {Weber, Rosina O. and Richter, Michael M.}, interhash = {640082e08bef8da18a136c2e948798c8}, intrahash = {7622cb7b536f9a556797b25917407c3b}, isbn = {978-3-540-74138-1}, issn = {0302-9743}, journal = {Case-Based Reasoning Research and Development}, keywords = {group-recommendation}, pages = {299--313}, posted-at = {2009-03-28 22:41:03}, priority = {2}, publisher = {Springer Berlin Heidelberg}, series = {Lecture Notes in Computer Science}, timestamp = {2018-03-19T12:24:51.000+0100}, title = {{Case-Based Group Recommendation: Compromising for Success}}, url = {http://dx.doi.org/10.1007/978-3-540-74141-1_21}, volume = 4626, year = 2007 }