arXiv Open Access 2018

Next Item Recommendation with Self-Attention

Shuai Zhang Yi Tay Lina Yao Aixin Sun

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Abstrak

In this paper, we propose a novel sequence-aware recommendation model. Our model utilizes self-attention mechanism to infer the item-item relationship from user's historical interactions. With self-attention, it is able to estimate the relative weights of each item in user interaction trajectories to learn better representations for user's transient interests. The model is finally trained in a metric learning framework, taking both short-term and long-term intentions into consideration. Experiments on a wide range of datasets on different domains demonstrate that our approach outperforms the state-of-the-art by a wide margin.

Topik & Kata Kunci

cs.IR

Penulis (4)

Shuai Zhang

Yi Tay

Lina Yao

Aixin Sun

Format Sitasi

APA MLA BibTeX

Zhang, S., Tay, Y., Yao, L., Sun, A. (2018). Next Item Recommendation with Self-Attention. https://arxiv.org/abs/1808.06414

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Informasi Jurnal

Tahun Terbit: 2018
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓