Preference inference based on lexicographic models
dc.contributor.author | Wilson, Nic | |
dc.contributor.editor | Schaub, Torsten | |
dc.contributor.editor | Friedrich, Gerhard | |
dc.contributor.editor | O'Sullivan, Barry | |
dc.contributor.funder | Science Foundation Ireland | en |
dc.date.accessioned | 2020-11-23T16:35:40Z | |
dc.date.available | 2020-11-23T16:35:40Z | |
dc.date.issued | 2014 | |
dc.date.updated | 2020-11-04T13:19:01Z | |
dc.description.abstract | With personalisation becoming more prevalent, it can often be useful to be able to infer additional preferences from input user preferences. Preference inference techniques assume a set of possible user preference models, and derive inferences that hold in all models satisfying the inputs; the more restrictive one makes the set of possible user preference models, the more inferences one gets. Sometimes it can be useful to have an adventurous form of preference inference when the input information is relatively weak, for example, in a conversational recommender system context, to give some justification for showing some options before others. This paper considers an adventurous inference based on assuming that the user preferences are lexicographic, and also an inference based on an even more restrictive preference model. We show how preference inference can be efficiently computed for these cases, based on a relatively general language of preference inputs. | en |
dc.description.status | Peer reviewed | en |
dc.description.version | Published Version | en |
dc.format.mimetype | application/pdf | en |
dc.identifier.citation | Wilson, N. (2014) 'Preference Inference Based on Lexicographic Models', 21st biennial European Conference on Artificial Intelligence, ECAI 2014, Prague, Czech Republic, August 18-21, in Frontiers in Artificial Intelligence and Applications, Volume 263: ECAI 2014, pp. 921 - 926. doi: 10.3233/978-1-61499-419-0-921 | en |
dc.identifier.doi | 10.3233/978-1-61499-419-0-921 | en |
dc.identifier.endpage | 926 | en |
dc.identifier.isbn | 978-1-61499-418-3 | |
dc.identifier.isbn | 978-1-61499-419-0 | |
dc.identifier.journaltitle | Frontiers in Artificial Intelligence and Applications | en |
dc.identifier.startpage | 921 | en |
dc.identifier.uri | https://hdl.handle.net/10468/10782 | |
dc.identifier.volume | 263 | en |
dc.language.iso | en | en |
dc.publisher | IOS Press | en |
dc.relation.ispartof | Frontiers in Artificial Intelligence and Applications | |
dc.relation.uri | http://ebooks.iospress.nl/volumearticle/37060 | |
dc.rights | © 2014 The Authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License. | en |
dc.rights.uri | https://creativecommons.org/licenses/by-nc/3.0/deed.en_US | en |
dc.subject | Preference inference techniques | en |
dc.subject | AI technology | en |
dc.subject | Artificial intelligence (AI) | en |
dc.title | Preference inference based on lexicographic models | en |
dc.type | Conference item | en |
Files
Original bundle
1 - 2 of 2
Loading...
- Name:
- Lex-inference-ECAI-2014.pdf
- Size:
- 297.35 KB
- Format:
- Adobe Portable Document Format
- Description:
- Author's original
Loading...
- Name:
- FAIA263-0921.pdf
- Size:
- 254.4 KB
- Format:
- Adobe Portable Document Format
- Description:
- Published version
License bundle
1 - 1 of 1
Loading...
- Name:
- license.txt
- Size:
- 2.71 KB
- Format:
- Item-specific license agreed upon to submission
- Description: