• Journal of Internet Computing and Services
    ISSN 2287 - 1136 (Online) / ISSN 1598 - 0170 (Print)
    https://jics.or.kr/

Digital Library


Search: "[ keyword: model ]" (142)
  1. 1. Analysis of Users’ Sentiments and Needs for ChatGPT through Social Media on Reddit
    Hye-In Na, Byeong-Hee Lee, Vol. 25, No. 2, pp. 79-92, Apr. 2024
    10.7472/jksii.2024.25.2.79
    Keywords: ChatGPT, Reddit, Needmining, sentiment analysis, topic modeling
  2. 2. Research on the Traveling Intention to Korea under the Background of Tourism Recovering, Based on Investigation on Foreigners in Korea
    Ming-ming Lin, Yu-min Jeong, Zi-yang Liu, Vol. 25, No. 2, pp. 69-77, Apr. 2024
    10.7472/jksii.2024.25.2.69
    Keywords: Tourism, e-Commerce, TAM model, Information Quality, perceived risk
  3. 3. Analysis of the Security Requirements of the Chatbot Service Implementation Model
  4. 4. An Exploratory Study on the Trustworthiness Analysis of Generative AI
    Soyon Kim, Ji Yeon Cho, Bong Gyou Lee, Vol. 25, No. 1, pp. 79-90, Feb. 2024
    10.7472/jksii.2024.25.1.79
    Keywords: Generative AI, ChatGPT, trust, Expectation-Confirmation Model, Continued Use Intention
  5. 5. Derivation of an effective military fitness model RSC clustering analysis method through review of e-commerce customers clustering analysis methods
    Junho Lee, Byung-in Roh, Dong-kyoo Shin, Vol. 24, No. 6, pp. 145-153, Dec. 2023
    10.7472/jksii.2023.24.6.145
    Keywords: Military, fitness, RFM customer analysis, RSC analysis model
  6. 6. A Study on Automatic Discovery and Summarization Method of Battlefield Situation Related Documents using Natural Language Processing and Collaborative Filtering
  7. 7. A Machine Learning-based Popularity Prediction Model for YouTube Mukbang Content
    Beomgeun Seo, Hanjun Lee, Vol. 24, No. 6, pp. 49-55, Dec. 2023
    10.7472/jksii.2023.24.6.49
    Keywords: Machine Learning, YouTube, Mukbang, Popularity Prediction, Predictive model
  8. 8. Proposal for the Hourglass-based Public Adoption-LinkedNational R&D Project Performance Evaluation Framework
  9. 9. Control-Path Driven Process-Group Discovery Framework and its Experimental Validation for Process Mining and Reengineering
  10. 10. A Study on Efficient AI Model Drift Detection Methods for MLOps
    Ye-eun Lee, Tae-jin Lee, Vol. 24, No. 5, pp. 17-27, Oct. 2023
    10.7472/jksii.2023.24.5.17
    Keywords: Artificail Inteligence, Machine Learning Model, Drift Detection, XAI, MLOps