Connecting social media to e-commerce : cold-start product recommendation using microblogging information
- Submitting institution
-
Aston University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 21462130
- Type
- D - Journal article
- DOI
-
10.1109/TKDE.2015.2508816
- Title of journal
- IEEE Transactions on Knowledge and Data Engineering
- Article number
- -
- First page
- 1147
- Volume
- 28
- Issue
- 5
- ISSN
- 1041-4347
- Open access status
- Out of scope for open access requirements
- Month of publication
- December
- Year of publication
- 2015
- 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
-
5
- Research group(s)
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A - Aston Institute of Urban Technology and the Environment (ASTUTE)
- Citation count
- 73
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Proposes a novel neural solution for cross-site cold-start product recommendation. The research has found applications in content dissemination in Intent-of-Vehicles (OV) networks (Instituto de Telecomunicacoes, Portugal) and web page recommendation (Verma, Delhi Technological University) and also impacted on cross-domain recommendation (Yu, Tsinghua), multi-platform topic analysis (Hoang, Leibniz University of Hanover; Lim, SMU), and product matching and categorisation (Yahoo Research Labs, Spain).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
