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Home > Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 36 > No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations

Conditional Collaborative Filtering Process for Top-K Recommender System (Student Abstract)

February 1, 2023

Authors

Guanyu Wang

University of Electronic Science and Technology of China


Xovee Xu

University of Electronic Science and Technology of China


Ting Zhong

University of Electronic Science and Technology of China


Fan Zhou

University of Electronic Science and Technology of China


Proceedings:

No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations

Volume

Issue:

Proceedings of the AAAI Conference on Artificial Intelligence, 36

Track:

AAAI Student Abstract and Poster Program

Downloads:

Download PDF

Abstract:

Conditional neural process (CNP) has been extensively applied into data analyzing tasks due to its excellent ability to make accurate predictions for incomplete data points. However, in literature there are only few works that studied the CNPin recommendation systems. In this work, we propose CCFP, which is a collaborative filtering method that differs from other CF models by incorporating CNP into encoder-decoder architecture. By analyzing the complete user-item interaction data, our model fits a global representation that can better rep-resenting the features of users and items. CCFP can significantly improve the recommendation performance compared to baselines by predicting items for the target users with their incomplete observation data.

DOI:

10.1609/aaai.v36i11.21673


AAAI

Proceedings of the AAAI Conference on Artificial Intelligence, 36



Topics: AAAI

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