Recurrent Point Processes for Dynamic Review Models
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.
- Published in:
WICRS Workshop at AAAI Workshop on Interactive and Conversational Recommendation Systems (WICRS) at AAAI Conference on Artificial Intelligence (AAAI) - Type:
Inproceedings - Authors:
K. Cvejoski, R. Sanchez, B. Georgiev, J. Schuecker, C. Bauckhage, C. Ojeda - Year:
2020
Citation information
K. Cvejoski, R. Sanchez, B. Georgiev, J. Schuecker, C. Bauckhage, C. Ojeda: Recurrent Point Processes for Dynamic Review Models, Workshop on Interactive and Conversational Recommendation Systems (WICRS) at AAAI Conference on Artificial Intelligence (AAAI), WICRS Workshop at AAAI, 2020, https://doi.org/10.48550/arXiv.1912.04132, Cvejoski.etal.2020a,
@Inproceedings{Cvejoski.etal.2020a,
author={K. Cvejoski, R. Sanchez, B. Georgiev, J. Schuecker, C. Bauckhage, C. Ojeda},
title={Recurrent Point Processes for Dynamic Review Models},
booktitle={Workshop on Interactive and Conversational Recommendation Systems (WICRS) at AAAI Conference on Artificial Intelligence (AAAI)},
journal={WICRS Workshop at AAAI},
url={https://doi.org/10.48550/arXiv.1912.04132},
year={2020},
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...}}