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Sentiment Analysis-based Recommendation System Architecture

Published: 03 May 2024 Publication History

Abstract

The goal of the Sentiment Analysis-based Recommendation System (SA-RS) is to extract or analyze people's emotions, opinions, thoughts, and other information regarding a certain object or event, and then utilize this information to achieve more personalized and accurate recommendations. With the rapid development of the Internet, a large amount of user-generated information has emerged online, containing abundant personal and group-related data from which we can analyze individual or collective preferences in order to realize more reasonable and precise recommendations. However, the integration of sentiment analysis with recommendation systems has not yet been addressed in a comprehensive manner due to the varying ideas surrounding novel methodologies. Therefore, we conducted a survey on past SA-RS to summarize a universally applicable structure for SA-RS. We hope this paper will provide clearer research ideas for future researchers in related fields. In addition to that, we provide detailed introductions on each step from data preprocessing to emotion models and recommendation models. We also classify existing sentiment analysis methods into two categories: centralized model and distributed model. Our aim is to systematically organize sentiment analysis models. Finally, our study presents several possible future research directions. We anticipate that our contribution may prove beneficial to researchers engaged in the realm of sentiment analysis or recommendation systems.

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  • (2024)Empowering E-commerce: Leveraging Open AI and Sentiment Analysis for Smarter Recommendations2024 International Conference on Electrical Electronics and Computing Technologies (ICEECT)10.1109/ICEECT61758.2024.10739003(1-5)Online publication date: 29-Aug-2024
  • (2024)Integrating Context and Criteria in Hotel Recommendations: A Deep Learning Perspective2024 International Conference on Computing, Sciences and Communications (ICCSC)10.1109/ICCSC62048.2024.10830411(1-5)Online publication date: 24-Oct-2024

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  1. Sentiment Analysis-based Recommendation System Architecture

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    cover image ACM Other conferences
    IoTAAI '23: Proceedings of the 2023 5th International Conference on Internet of Things, Automation and Artificial Intelligence
    November 2023
    902 pages
    ISBN:9798400716485
    DOI:10.1145/3653081
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    Published: 03 May 2024

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    • (2024)Empowering E-commerce: Leveraging Open AI and Sentiment Analysis for Smarter Recommendations2024 International Conference on Electrical Electronics and Computing Technologies (ICEECT)10.1109/ICEECT61758.2024.10739003(1-5)Online publication date: 29-Aug-2024
    • (2024)Integrating Context and Criteria in Hotel Recommendations: A Deep Learning Perspective2024 International Conference on Computing, Sciences and Communications (ICCSC)10.1109/ICCSC62048.2024.10830411(1-5)Online publication date: 24-Oct-2024

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