Collaborative Multi-key Learning with an Anonymization Dataset for a Recommender System

Linh Nguyen, Tsukasa Ishigaki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Balancing accuracy and privacy is an important tradeoff problem for information systems, including recommender systems. To achieve high performance, modern recommender systems tend to use as much information as possible. This trend is borne out by the increasing number of studies of hybrid methods that combine rating and auxiliary information. However, because of privacy concerns, in many cases, service providers can not require users to give their personal information. Therefore, numerous earlier reported methods only use item attributes for auxiliary information. To address these shortcomings, our manuscript provides a method to extract user profiles without using demographic data. Our model learns user and item latent variables through two separate deep neural networks and also learns implicit relations between users and items using the information and their ratings. Experiments verified that our model is a more effective recommender system than state-of- the-art baselines.

Original languageEnglish
Title of host publication2019 International Joint Conference on Neural Networks, IJCNN 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728119854
DOIs
Publication statusPublished - 2019 Jul
Event2019 International Joint Conference on Neural Networks, IJCNN 2019 - Budapest, Hungary
Duration: 2019 Jul 142019 Jul 19

Publication series

NameProceedings of the International Joint Conference on Neural Networks
Volume2019-July

Conference

Conference2019 International Joint Conference on Neural Networks, IJCNN 2019
CountryHungary
CityBudapest
Period19/7/1419/7/19

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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  • Cite this

    Nguyen, L., & Ishigaki, T. (2019). Collaborative Multi-key Learning with an Anonymization Dataset for a Recommender System. In 2019 International Joint Conference on Neural Networks, IJCNN 2019 [8852157] (Proceedings of the International Joint Conference on Neural Networks; Vol. 2019-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IJCNN.2019.8852157