loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Natsumi Baba ; Yuichi Sei ; Yasuyuki Tahara and Akihiko Ohsuga

Affiliation: The University of Electro-Communications, Tokyo, Japan

Keyword(s): Collaborative Filtering, Morphological Analysis, Review Analysis, Product Recommendation.

Abstract: There are a variety of product introduction sites on the Internet, and many of these usually provide a combination of product composition information and user review text. It is difficult to understand the features of a product in detail from the information on these sites. Furthermore, these review sites often include product recommendations such as "recommended for you," but often lack an explanation of why the product is recommended. Therefore, this study proposes an approach that provides both the user’s opinion of the product and the reason for recommending the product in a simplified manner. Using cosmetics as a case study, where the user’s actual experience is important, we scored product features on a 5-point scale based on review submitted by users. This data was used for collaborative filtering to determine product recommendations and generate review sentences that target users are expected to write when using the product. The generated reviews facilitate users to understan d the details of a product before purchasing it and are useful for comparison before purchasing a product. To verify the usefulness of the proposed method, we conducted a questionnaire comparing it with existing methods. The proposed method aims to improve user satisfaction in product recommendations. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 44.221.73.157

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Baba, N.; Sei, Y.; Tahara, Y. and Ohsuga, A. (2024). Proposal of a Cosmetic Product Recommendation Method with Review Text that is Predicted to Be Write by Users. In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-680-4; ISSN 2184-433X, SciTePress, pages 609-616. DOI: 10.5220/0012377500003636

@conference{icaart24,
author={Natsumi Baba. and Yuichi Sei. and Yasuyuki Tahara. and Akihiko Ohsuga.},
title={Proposal of a Cosmetic Product Recommendation Method with Review Text that is Predicted to Be Write by Users},
booktitle={Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2024},
pages={609-616},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012377500003636},
isbn={978-989-758-680-4},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Proposal of a Cosmetic Product Recommendation Method with Review Text that is Predicted to Be Write by Users
SN - 978-989-758-680-4
IS - 2184-433X
AU - Baba, N.
AU - Sei, Y.
AU - Tahara, Y.
AU - Ohsuga, A.
PY - 2024
SP - 609
EP - 616
DO - 10.5220/0012377500003636
PB - SciTePress