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https://scholarbank.nus.edu.sg/handle/10635/238636
DC Field | Value | |
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dc.title | TOWARDS EFFECTIVE MODELING OF SUCCESSIVE PREFERENCES | |
dc.contributor.author | LIM XIANG HUI NICHOLAS | |
dc.date.accessioned | 2023-03-31T18:00:56Z | |
dc.date.available | 2023-03-31T18:00:56Z | |
dc.date.issued | 2022-09-28 | |
dc.identifier.citation | LIM XIANG HUI NICHOLAS (2022-09-28). TOWARDS EFFECTIVE MODELING OF SUCCESSIVE PREFERENCES. ScholarBank@NUS Repository. | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/238636 | |
dc.description.abstract | The increased popularity of web-based platforms, has led to an unprecedented surge of users who perform various activities on these platforms, and therefore, the availability of massive user-related datasets which describe their latent preferences and behaviors. For instance, a rising research interest looks at the modeling of successive preferences from users' sequential data streams, to best learn and provide recommendations, such as recommending the next Point-of-Interest (POI) or location to users from their historical successive visit patterns. However, effective modeling of users' successive preferences remains a challenging task due to various hurdles, which include balancing the explore-exploit trade-offs, data sparsity, the highly dynamic behavioral patterns of users, and others. In this thesis, we will look at three main approaches to model successive preferences, with different location recommendation applications. | |
dc.language.iso | en | |
dc.subject | Successive Preferences, Next POI Recommendation, Spatio-temporal, Graph Neural Networks, Recommender Systems | |
dc.type | Thesis | |
dc.contributor.department | COMPUTER SCIENCE | |
dc.contributor.supervisor | See Kiong Ng | |
dc.contributor.supervisor | Kuen-Yew Bryan Hooi | |
dc.description.degree | Ph.D | |
dc.description.degreeconferred | DOCTOR OF PHILOSOPHY (SOC) | |
dc.identifier.orcid | 0000-0001-9323-1091 | |
Appears in Collections: | Ph.D Theses (Open) |
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LimXHN.pdf | 10.03 MB | Adobe PDF | OPEN | None | View/Download |
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