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Research Output Details
| Forouzandeh, S and Aghdam, AR and Xu, S and Forouzandeh, S, “Addressing the cold-start problem using data mining techniques and improving recommender systems by Cuckoo algorithm: a case study of Facebook”, Computing in Science and Engineering, 22 (4) pp. 62-73. ISSN 1521-9615 (2020) [Refereed Article] | |
| Data Type | Value |
|---|---|
| Type of Research | Applied Research |
| Research Division | Information and Computing Sciences |
| Research Group | Computer vision and multimedia computation |
| Research Field | Pattern recognition |
| Research Objective Division | Information and Communication Services |
| Research Objective Group | Information systems, technologies and services |
| Research Objective Field | Information systems, technologies and services not elsewhere classified |
| Visit Item on eCite | http://ecite.utas.edu.au/139552 |
| Digital Object Identifier | doi:10.1109/MCSE.2018.2875321 |
| Scopus Source URL | View the full record on Scopus |
| Scopus Citing URL | View the list of citing articles on Scopus |
| Web of Science® Source URL | View the full record on Web of Science® |
| Web of Science® Citing URL | View the list of citing articles on Web of Science® |
| Web of Science® Related URL | View the list of related articles on Web of Science® |
| Number of Times Cited | 10 |