Generating top-k packages via preference elicitation
- Submitting institution
-
Birkbeck College
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 202
- Type
- D - Journal article
- DOI
-
10.14778/2733085.2733099
- Title of journal
- Proceedings of the VLDB Endowment
- Article number
- -
- First page
- 1941
- Volume
- 7
- Issue
- 14
- ISSN
- 2150-8097
- Open access status
- Out of scope for open access requirements
- Month of publication
- October
- Year of publication
- 2015
- URL
-
http://eprints.bbk.ac.uk/id/eprint/10941/
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
-
3 - Knowledge Representation and Data Management
- Citation count
- 8
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper addresses the problem of recommending sets (or packages) of items to users by learning the user’s preferences through interaction with proposed packages. This approach overcomes the problems of previous approaches which either required unrealistic hard constraints to be specified by a user or returned too many packages. The paper was accepted for presentation at the 41st International Conference on Very Large Databases in 2015, a premier database conference for which the acceptance rate for research papers was 21.3%.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -