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| Presentation | 2022-07-14 13:35 Building a Federated Personalized Recommendation Model to Balance Similarity and Diversity Masahiro Hamada, Taisho Sasada, Yuzo Taenaka, Youki Kadobayashi (NAIST)  NS2022-46 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | With the spread of on-demand movie distribution, personalized movie recommendations that match user preferences are required to improve service quality and retention rates. In recent years, it has become clear that the retention rate can be improved by recommending not only movies similar to the user’s favorite movies. Diversity is also used as an important indicator ．In general, movie recommendation uses viewing history and evaluation scores to select recommended movies, and video distributors must store and use user information. However, based on EU General Data Protection Regulation (GDPR), there are restrictions on the retention and use of such data that can be used to infer personal tastes and thoughts, and this creates a problem that individualized movie recommendations cannot be made based on the user’s viewing log. In contrast, the use of Federative Learning (FL), which can recommend movies without holding data, has been attracting attention, but since training data is trained on the user’s terminal, it tends to learn too much about the tendencies of each terminal. Therefore, we propose a method for constructing a privacy protection recommendation model that achieves both similarity and diversity. By selecting training data in a way that does not impair either similarity or diversity, and building a mechanism for learning on each terminal, we aim to construct a privacy-protective recommendation model that recommends a variety of movies while maintaining similarity to the browsing log. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Federated Leanring / Bayesian Personalized Ranking / Matrix Factorization / Recommender System / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 105, NS2022-46, pp. 100-105, July 2022. | |
| Paper # | NS2022-46 | |
| Date of Issue | 2022-07-06 (NS) | |
| ISSN | Online edition: ISSN 2432-6380 | |
| Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| Download PDF | NS2022-46 |
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| Conference Information | |
| Committee | NS SR RCS SeMI RCC |
| Conference Date | 2022-07-13 - 2022-07-15 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | The Kanazawa Theatre + Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Distributed Wireless Network, M2M (Machine-to-Machine)，D2D (Device-to-Device)，IoT（Internet of Things）, etc |
| Paper Information | |
| Registration To | NS |
| Conference Code | 2022-07-NS-SR-RCS-SeMI-RCC |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Building a Federated Personalized Recommendation Model to Balance Similarity and Diversity |
| Sub Title (in English) | |
| Keyword(1) | Federated Leanring |
| Keyword(2) | Bayesian Personalized Ranking |
| Keyword(3) | Matrix Factorization |
| Keyword(4) | Recommender System |
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| 1st Author's Name | Masahiro Hamada |
| 1st Author's Affiliation | Nara Institute of Science and Technology (NAIST) |
| 2nd Author's Name | Taisho Sasada |
| 2nd Author's Affiliation | Nara Institute of Science and Technology (NAIST) |
| 3rd Author's Name | Yuzo Taenaka |
| 3rd Author's Affiliation | Nara Institute of Science and Technology (NAIST) |
| 4th Author's Name | Youki Kadobayashi |
| 4th Author's Affiliation | Nara Institute of Science and Technology (NAIST) |
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| Speaker | Author-1 |
| Date Time | 2022-07-14 13:35:00 |
| Presentation Time | 25 minutes |
| Registration for | NS |
| Paper # | NS2022-46 |
| Volume (vol) | vol.122 |
| Number (no) | no.105 |
| Page | pp.100-105 |
| #Pages | 6 |
| Date of Issue | 2022-07-06 (NS) |
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