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Deep Learning for Sequential Recommendation: Algorithms, Influential Factors, and Evaluations
[article]
2020
arXiv
pre-print
In the field of sequential recommendation, deep learning (DL)-based methods have received a lot of attention in the past few years and surpassed traditional models such as Markov chain-based and factorization-based ones. However, there is little systematic study on DL-based methods, especially regarding to how to design an effective DL model for sequential recommendation. In this view, this survey focuses on DL-based sequential recommender systems by taking the aforementioned issues into
arXiv:1905.01997v3
fatcat:i7hvdiqjpnaupcq2osrblttb4u