Generating Experiential Descriptions and Estimating Evidence Using Generative Language Model and User Products Reviews-Reference-Cited by-同舟云学术

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Generating Experiential Descriptions and Estimating Evidence Using Generative Language Model and User Products Reviews

Published:2024-02-18 Issue: Volume: Page:254-261
ISSN:
Container-title:2024 IEEE International Conference on Big Data and Smart Computing (BigComp)
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Author:

Chenfu Shen¹,Shoji Yoshiyuki²,Yamamoto Takehiro³,Tanaka Katsumi²,Dürst Martin J.⁴

Affiliation:

1. Graduate School of Science and Engineering, Aoyama Gakuin University,Kanagawa,Japan

2. Shizuoka University,Faculty of Informatics,Shizuoka,Japan

3. School of Social Information Science, University of Hyogo,Kobe,Japan

4. College of Science and Engineering, Aoyama Gakuin University,Kanagawa,Japan

Funder

JSPS KAKENHI

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10488103/10488104/10488256.pdf?arnumber=10488256

Reference10 articles.

1. Joint Deep Modeling of Users and Items Using Reviews for Recommendation

2. Automatic Product Copywriting for E-commerce

3. Improve Diverse Text Generation by Self Labeling Conditional Variational Auto Encoder

4. The role of transparency in recommender systems

5. Selection and generation: Learning towards multi-product advertisement post generation;Chan,2020

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