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Authors: Hanxuan Chen and Zuoquan Lin

Affiliation: Department of Information Science, School of Mathematical Sciences, Peking University, Beijing 100871, China

ISBN: 978-989-758-350-6

Keyword(s): Hidden Markov Model, Neural Network, Collaborative Filtering, Recommender Systems.

Abstract: In this paper, we propose a hybrid model that combines neural network and hidden Markov model for time-aware recommender systems. We use higher-order hidden Markov model to capture the temporal information of users and items in collaborative filtering systems. Because the computation of the transition matrix of higher-order hidden Markov model is hard, we compute the transition matrix by deep neural networks. We implement the algorithms of the hybrid model for offline batch-learning and online updating respectively. Experiments on real datasets demonstrate that the hybrid model has improvement performances over the existing recommender systems.

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Paper citation in several formats:
Chen, H. and Lin, Z. (2019). A Hybrid Neural Network and Hidden Markov Model for Time-aware Recommender Systems.In Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-350-6, pages 204-213. DOI: 10.5220/0007380402040213

@conference{icaart19,
author={Hanxuan Chen. and Zuoquan Lin.},
title={A Hybrid Neural Network and Hidden Markov Model for Time-aware Recommender Systems},
booktitle={Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2019},
pages={204-213},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007380402040213},
isbn={978-989-758-350-6},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - A Hybrid Neural Network and Hidden Markov Model for Time-aware Recommender Systems
SN - 978-989-758-350-6
AU - Chen, H.
AU - Lin, Z.
PY - 2019
SP - 204
EP - 213
DO - 10.5220/0007380402040213

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