Dual Intent Enhanced Graph Neural Network for Session-based New Item Recommendation

Author:

Jin Di1ORCID,Wang Luzhi1ORCID,Zheng Yizhen2ORCID,Song Guojie3ORCID,Jiang Fei4ORCID,Li Xiang5ORCID,Lin Wei5ORCID,Pan Shirui6ORCID

Affiliation:

1. College of Intelligence and Computing, Tianjin University, China

2. Department of Data Science and AI, Faculty of IT, Monash University, Australia

3. School of Intelligence Science and Technology, Peking University, China

4. Meituan, China

5. Professional, China

6. School of Information and Communication Technology, Griffith University, Australia

Funder

Natural Science Foundation of China

Meituan Project

Publisher

ACM

Reference41 articles.

1. Automated Generation of Music Playlists;Bonnin Geoffray;Survey and Experiments. ACM Computing Surveys,2014

2. Clicks can be Cheating: Counterfactual Recommendation for Mitigating Clickbait Issue

3. [ 3 ] Balázs Hidasi , Alexandros Karatzoglou , Linas Baltrunas , and Domonkos Tikk. Session-based Recommendations with Recurrent Neural Networks In International Conference on Learning Representations , 2016 . [3] Balázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, and Domonkos Tikk. Session-based Recommendations with Recurrent Neural Networks In International Conference on Learning Representations, 2016.

4. Evaluation of session-based recommendation algorithms

5. [ 5 ] David Arthur and Sergei Vassilvitskii . k-means++ : The advantages of careful seeding. Technical report , Stanford , 2006 . [5] David Arthur and Sergei Vassilvitskii. k-means++: The advantages of careful seeding. Technical report, Stanford, 2006.

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