Hete-CF : Social-Based Collaborative Filtering Recommendation using Heterogeneous Relations
- Submitting institution
-
University of Aberdeen
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 70071316
- Type
- E - Conference contribution
- DOI
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10.1109/ICDM.2014.64
- Title of conference / published proceedings
- 2014 IEEE International Conference on Data Mining
- First page
- 917
- Volume
- -
- Issue
- -
- ISSN
- 1550-4786
- Open access status
- Out of scope for open access requirements
- Month of publication
- December
- Year of publication
- 2014
- 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
-
3
- Research group(s)
-
-
- Citation count
- 39
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- ICDM is a top-tier conference in data mining. In this paper, we proposed a novel algorithm for social-based collaborative filtering by considering heterogeneous relations, which yields substantial improvement in recommendation accuracy when compared to existing algorithms which consider homogenous relations only.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
