Recurrent Point Processes for Dynamic Review Models
Abstract
Recent progress in recommender system research has shown the importance of including temporal representations to improve interpretability and performance. Here, we incorporate temporal representations in continuous time via recurrent point process for a dynamical model of reviews. Our goal is to characterize how changes in perception, user interest and seasonal effects affect review text.
- Publication:
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arXiv e-prints
- Pub Date:
- December 2019
- DOI:
- 10.48550/arXiv.1912.04132
- arXiv:
- arXiv:1912.04132
- Bibcode:
- 2019arXiv191204132C
- Keywords:
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- Computer Science - Machine Learning;
- Statistics - Machine Learning
- E-Print:
- Presented at the AAAI 2020 Workshop on Interactive and Conversational Recommendation Systems