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Jul 9, 2020 · Experiments demonstrate that our model achieves promising results for recommendation on few-shot users with limited training ratings and new ...
We frame the problem as open-world recommendation which requires the model to deal with few-shot and zero-shot users. We present our model framework for two ...
This work proposes a new collaborative filtering approach for recsys. The new method could achieve inductive learning for new users in testing set.
PDF | On Apr 10, 2021, Qitian Wu and others published Towards Open-World Recommendation: An Inductive Model-based Collaborative Filtering Approach | Find, ...
This work explores the role of the fine-grained item attributes in bridging the gaps between the existing and the SCS items and proposes ColdGPT, ...
Mar 7, 2022 · We frame the problem as open-world recommendation which requires the model to deal with few-shot and zero-shot users. We present our model ...
Towards Open-World Recommendation: An Inductive Model-based. Collaborative Filtering Approach. Qitian Wu, Hengrui Zhang, Xiaofeng Gao, Junchi Yan, Hongyuan ...
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We compare IDCF with other related models from two per- spectives in order to shed more lights on the advantages and differences of our model.
Towards Open-World Recommendation: An Inductive Model-based Collaborative Filtering Approach. Qitian Wu, Hengrui Zhang, Xiaofeng Gao, Junchi Yan, Hongyuan ...
Towards open-world recommendation: An inductive model-based collaborative filtering approach. Q Wu, H Zhang, X Gao, J Yan, H Zha. International Conference on ...