A 2020 perspective on “A generalized stereotype learning approach and its instantiation in trust modeling”
dc.contributor.author | Fang, H. | |
dc.contributor.author | Zhang, J. | |
dc.contributor.author | Şensoy, Murat | |
dc.date.accessioned | 2021-01-28T10:01:39Z | |
dc.date.available | 2021-01-28T10:01:39Z | |
dc.date.issued | 2020-03 | |
dc.identifier.issn | 1567-4223 | en_US |
dc.identifier.uri | http://hdl.handle.net/10679/7239 | |
dc.identifier.uri | https://www.sciencedirect.com/science/article/abs/pii/S1567422320300326 | |
dc.description.abstract | Owing to the rapid increase of user data and development of machine learning techniques, user modeling has been explored in depth and exploited by both academia and industry. It has prominent impacts in e-commercerelated applications by facilitating users' experience in online platforms and supporting business organizations' decision-making. Among all the techniques and applications, user profiling and recommender systems are two representative and effective ones, which have also obtained growing attention. In view of its wide applications, researchers and practitioners should improve user modeling from two perspectives: (1) more effort should be devoted to obtain more user data via techniques like sensing devices and develop more effective ways to manage complex data; and (2) improving the ability of learning from a limited number of data samples (e.g., few-shot learning) has become an increasingly hot topic for researchers. | en_US |
dc.description.sponsorship | National Natural Science Foundation of China (NSFC) | |
dc.language.iso | eng | en_US |
dc.publisher | Elsevier | en_US |
dc.relation.ispartof | Electronic Commerce Research and Applications | |
dc.rights | restrictedAccess | |
dc.title | A 2020 perspective on “A generalized stereotype learning approach and its instantiation in trust modeling” | en_US |
dc.type | Article | en_US |
dc.peerreviewed | yes | en_US |
dc.publicationstatus | Published | en_US |
dc.contributor.department | Özyeğin University | |
dc.contributor.authorID | (ORCID 0000-0001-8806-4508 & YÖK ID 41438) Şensoy, Murat | |
dc.contributor.ozuauthor | Şensoy, Murat | |
dc.identifier.volume | 40 | en_US |
dc.identifier.wos | WOS:000528943600034 | |
dc.identifier.doi | 10.1016/j.elerap.2020.100955 | en_US |
dc.subject.keywords | Data management | en_US |
dc.subject.keywords | Few-shot learning | en_US |
dc.subject.keywords | Learning with limited data | en_US |
dc.subject.keywords | Recommender systems | en_US |
dc.subject.keywords | User modeling | en_US |
dc.subject.keywords | User profiling | en_US |
dc.subject.keywords | User profiling | en_US |
dc.identifier.scopus | SCOPUS:2-s2.0-85079555814 | |
dc.contributor.authorMale | 1 | |
dc.relation.publicationcategory | Article - International Refereed Journal - Institutional Academic Staff |
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