•  
  •  
 

International Journal of Computer Science and Informatics

Abstract

In this paper, we employed Naïve Bayes, Augmented Naïve Bayes, Tree Augmented Naïve Bayes, Sons & Spouses, Markov Blanket, Augmented Markov Blanket, Semi Supervised and Bayesian network techniques to rank web services. The Bayesian Network is demonstrated on a dataset taken from literature. The dataset consists of 364 web services whose quality is described by 9 attributes. Here, the attributes are treated as criteria, to classify web services. From the experiments, we conclude that Naïve based Bayesian network performs better than other two techniques comparable to the classification done in literature.

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.