首页    期刊浏览 2024年12月03日 星期二
登录注册

文章基本信息

  • 标题:Statistical Analysis and Learning Method on Users' Feedbacks
  • 本地全文:下载
  • 作者:Wong, Doris Hooi-Ten ; Ramadass, Sureswaran
  • 期刊名称:Journal of Computer Science
  • 印刷版ISSN:1549-3636
  • 出版年度:2011
  • 卷号:7
  • 期号:9
  • 页码:1423-1425
  • DOI:10.3844/jcssp.2011.1423.1425
  • 出版社:Science Publications
  • 摘要:Problem statement: The purpose of this study was constructing an effective algorithm in order to learn the users’ feedbacks from their displayed visualization. This is due to existing visualization tools typically involve presenting network data regardless of considering level of network data knowledge among different levels of computer users. The machine learning algorithm has been applied in order to find the most effective statistical analysis and learning algorithm in learning users’ feedbacks. Approach: The objectives of this study were to conduct statistical analysis and learning algorithm model for different levels of computer users’ feedbacks and procedure to test the classifier. Results: WEKA the machine learning workbench that supports many activities of machine learning practitioners will be used to implement the proposed algorithm. The implemented program will work as training testing model. Conclusion: We can produce an adaptive visualization to the different levels of computer users as we have learnt their feedbacks (behavior) and update the classifier model.
  • 关键词:Statistical analysis; learning method; user feedback; machine learning; effective algorithm; displayed visualization; existing visualization; network data; different levels of computer; learning algorithm
国家哲学社会科学文献中心版权所有