• Corpus ID: 219708890

User Profiling from Reviews for Accurate Time-Based Recommendations

@article{Alkan2020UserPF,
  title={User Profiling from Reviews for Accurate Time-Based Recommendations},
  author={Oznur Kirmemis Alkan and Elizabeth M. Daly},
  journal={ArXiv},
  year={2020},
  volume={abs/2006.08805}
}
Recommender systems are a valuable way to engage users in a system, increase participation and show them resources they may not have found otherwise. One significant challenge is that user interests may change over time and certain items have an inherently temporal aspect. As a result, a recommender system should try and take into account the time-dependant user-item relationships. However, temporal aspects of a user profile may not always be explicitly available and so we may need to infer… 

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