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This study explores the correlation between communal user needs and Quality of Service (QoS) across various technological domains. We collected online user reviews for smartphones and Social Network Services (SNS), key products and services in today’s society, to determine user needs for each domain. QoS parameters for each domain were chosen based on related research. The BERT (Bidirectional Encoder Representations from Transformers) model was used for word embedding to identify how users articulate QoS parameters and user needs, forming a database. Word2vec was used to analyze the correlation between user needs and QoS parameters, represented as a correlation map. This correlation map was then used to create a relationship map of QoS parameters, domain-specific user needs, and communal user needs. The findings confirmed the potential to map QoS parameters from specific domains to communal user needs. This method provides insights into the correlation between user needs and QoS parameters, aiding in identifying parameters that can enhance user satisfaction and engagement across various technologies.

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A Study to Explore How Communal User Needs and Quality of Service Related Across Various Domains Using Text Mining

  • 会议论文

  • 发表日期：

    2025年

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  • Seong-Taek Kim,
  • In-Seok Heo,
  • Beom-Su Kim,
  • Karur Krishna Sahithi,
  • Alivia Kirana Hartono Putri,
  • Minjun Kim,
  • Sang-ho Kim

摘要

This study explores the correlation between communal user needs and Quality of Service (QoS) across various technological domains. We collected online user reviews for smartphones and Social Network Services (SNS), key products and services in today’s society, to determine user needs for each domain. QoS parameters for each domain were chosen based on related research. The BERT (Bidirectional Encoder Representations from Transformers) model was used for word embedding to identify how users articulate QoS parameters and user needs, forming a database. Word2vec was used to analyze the correlation between user needs and QoS parameters, represented as a correlation map. This correlation map was then used to create a relationship map of QoS parameters, domain-specific user needs, and communal user needs. The findings confirmed the potential to map QoS parameters from specific domains to communal user needs. This method provides insights into the correlation between user needs and QoS parameters, aiding in identifying parameters that can enhance user satisfaction and engagement across various technologies.