Feb 28, 2022 · In our empirical experiments, we find that filtering algorithms can substantially improve representative sequential recommendation models, and ...
Motivated by it, we propose FMLP-Rec, an all-MLP model with learnable filters for sequential recommendation task. The all-MLP architecture endows our model with ...
In this section, we conduct an empirical study to test: (1) the ef- fectiveness of filtering algorithms in sequential recommendation models, and (2) the ...
Duration: 17:42
Posted: Sep 12, 2022
Posted: Sep 12, 2022
Filter-enhanced MLP is All You Need for Sequential Recommendation. Published in WWW 2022 Research Track, 2022. Kun Zhou*, Hui Yu*, Wayne Xin Zhao and Ji-Rong ...
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The source code for our WWW 2022 Paper "Filter-enhanced MLP is All You Need for Sequential Recommendation". Requirements. Install Python, Pytorch(>=1.8). We use ...
In this work, we propose a novel sequential recom- mender system (MLP4Rec) based on the recent advances of MLP-based architectures, which is naturally sensitive ...
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(2022) developed a filter-enhanced MLP framework for sequential recommendation, which obtains comparable results by integrating learnable filters.