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2004.01646
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M2: Mixed Models with Preferences, Popularities and Transitions for
Next-Basket Recommendation

v1v2v3v4 (latest)

M2: Mixed Models with Preferences, Popularities and Transitions for Next-Basket Recommendation

IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020

3 April 2020

Srinivas Parthasarathy

ArXiv (abs)PDF HTML

Papers citing "M2: Mixed Models with Preferences, Popularities and Transitions for Next-Basket Recommendation"

5 / 5 papers shown

Hypergraph Enhanced Knowledge Tree Prompt Learning for Next-Basket
Recommendation

Hypergraph Enhanced Knowledge Tree Prompt Learning for Next-Basket Recommendation

Chang-Dong Wang

Philip S. Yu

181

1

0

26 Dec 2023

Mutual Wasserstein Discrepancy Minimization for Sequential
Recommendation

Mutual Wasserstein Discrepancy Minimization for Sequential RecommendationThe Web Conference (WWW), 2023

Hao Peng

Philip S Yu

360

22

0

28 Jan 2023

Sequential Recommendation with Auxiliary Item Relationships via
Multi-Relational Transformer

Sequential Recommendation with Auxiliary Item Relationships via Multi-Relational Transformer

Hao Peng

Philip S. Yu

280

9

0

24 Oct 2022

Continuous-Time Sequential Recommendation with Temporal Graph
Collaborative Transformer

Continuous-Time Sequential Recommendation with Temporal Graph Collaborative TransformerInternational Conference on Information and Knowledge Management (CIKM), 2021

Philip S. Yu

311

222

0

14 Aug 2021

Modeling Sequences as Distributions with Uncertainty for Sequential
Recommendation

Modeling Sequences as Distributions with Uncertainty for Sequential RecommendationInternational Conference on Information and Knowledge Management (CIKM), 2021

Philip S. Yu

259

66

0

11 Jun 2021

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