FoodS and FoodIM: Food-Testing Item Recommendation Models for Two Different Users with Different Usage Abilities-Reference-Cited by-同舟云学术

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FoodS and FoodIM: Food-Testing Item Recommendation Models for Two Different Users with Different Usage Abilities

Published:2023-10-27 Issue: Volume:36 Page:1-9
ISSN:
Container-title:Proceedings of the 2023 4th Asia Service Sciences and Software Engineering Conference
language:
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Author:

Qi Zhixiao¹^ORCID,Huang Yongfeng²^ORCID,Wu Jinzhu³^ORCID,Li Songbin⁴^ORCID

Affiliation:

1. Department of Automation, Tsinghua University, China

2. Zhongguancun Laboratory, China and Department of Electronic Engineering, Tsinghua University, China

3. Department of Electronic Engineering, Tsinghua University, China

4. Haikou Lab, Institute of Acoustics, Chinese Academy of Sciences, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3634814.3634815

Reference32 articles.

1. Item-based collaborative filtering recommendation algorithms

2. The wisdom of the few

3. Hanani U., Shapira B., Shoval P. 2001. Information Filtering: Overview of Issues, Research and Systems. User modeling and user-adapted interaction, pp. 203-259.

4. A Multi-Purpose Ontology-Based Approach for Personalized Content Filtering and Retrieval

5. Si L., R. Jin. 2003. Flexible mixture model for collaborative filtering. Proceedings of the 20th International Conference on Machine Learning (ICML-03), pp. 704-711.

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