文章基本信息

标题：Opinion mining framework using proposed RB-Bayes model for text classication
其他标题：Opinion mining framework using proposed RB-Bayes model for text classication
作者：Rajni Bhalla ; Amandeep Bagga
期刊名称：International Journal of Electrical and Computer Engineering
电子版ISSN：2088-8708
出版年度：2018
卷号：9
期号：1
DOI：10.11591/ijece.v9i1.pp%p
语种：English
出版社：Institute of Advanced Engineering and Science (IAES)
摘要：Information mining is a capable idea with incredible potential to anticipate future patterns and conduct. It alludes to the extraction of concealed information from vast data sets by utilizing procedures like factual examination, machine learning, grouping, neural systems and genetic algorithms. In nave bayes, there exists a problem of zero likelihood. This paper proposed RB-Bayes method based on bayes theorem for prediction to remove problem of zero likelihood. We also compare our method with few existing methods i.e. naive bayes and SVM. We demonstrate that this technique is better than some current techniques and specically can analyze data sets in better way. At the point when the proposed approach is tried on genuine data-sets, the outcomes got improved accuracy in most cases. RB-Bayes calculation having precision 83.333.
关键词：Data mining;Information extraction;Sentiment mining;Classification;Naive Bayes; RB-Bayes; SVM; hotencoder