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Dangsawang, B. and Nuchitprasitchai, S. (2024) A Machine Learning Approach for Detecting Customs Fraud through Unstructured Data Analysis in Social Media. Decision Analytics Journal, 10, Article ID: 100408.
https://doi.org/10.1016/j.dajour.2024.100408

has been cited by the following article:

• TITLE: Research and Construction of Personalized Sleep Model Based on Questionnaire Data

  AUTHORS: Feng Ji, Yuan An, Yawen Xing, Haoran Guan, Sitian Yang, Panfeng Yuan

  KEYWORDS: Sleep Model, Personalization, Questionnaire Survey, Data Analysis

  JOURNAL NAME: Journal of Computer and Communications, Vol.12 No.11, November 21, 2024

  ABSTRACT: The purpose of this study is to investigate the sleep habits, cervical health status, and the demand and preference for pillow products of different populations through data analysis. A total of 780 valid responses were gathered via an online questionnaire to explore the sleep habits, cervical health conditions, and pillow product preferences of modern individuals. The study found that sleeping late and staying up late are common, and the use of electronic devices and caffeine consumption have a negative impact on sleep. Most respondents have cervical discomfort and have varying satisfaction with pillows, which shows their demand for personalized pillows. The machine learning model for predicting the demand of latex pillow was constructed and optimized to provide personalized pillow recommendation, aiming to improve sleep quality and provide market data for sleep product developers.