A Novel Classification Framework for Evaluating Individual and Aggregate Diversity in Top-N Recommendations
- Submitting institution
-
University of Ulster
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 76472311
- Type
- D - Journal article
- DOI
-
10.1145/2700491
- Title of journal
- ACM Transactions on Intelligent Systems and Technology
- Article number
- 42
- First page
- 1
- Volume
- 7
- Issue
- 3
- ISSN
- 2157-6904
- Open access status
- Out of scope for open access requirements
- Month of publication
- February
- Year of publication
- 2016
- URL
-
-
- 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
-
1
- Research group(s)
-
B - Artificial Intelligence Research Centre
- Citation count
- 6
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- <17> This work was developed out of a PhD project. The PhD candidate who was the first author of the paper completed her PhD in 2011 and subsequently worked as a teaching fellow in the School of Computing at Ulster from 2013 to 2016. The proposed approach to diversity has been used in other research (https://doi.org/10.1145/3231465).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -