Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/2402
Title: Quality Assessment of Web Services Using Multivariate Adaptive Regression Splines
Authors: Kumar, L
Rath, S K
Keywords: ANN
MARS
MLR
MPR
Naives Bayes
Web Service
WSRF
Issue Date: Dec-2015
Citation: Asia-Pacific Software Engineering Conference (APSEC 2015), New Delhi, India,1-4 December 2015
Abstract: The need to chose a suitable web service in the present scenario, due to the high growth in number of web services that provide similar types of functionalities is a critical task. To select a suitable web service, quality of service (QoS) parameters are efficient to use. In this paper, nine parameters of QoS have been considered as input for design a model using multivariate adaptive regression splines (MARS) to select suitable web service. The performance parameters of MARS model are evaluated and compared with those obtained using models such as: Multivariate Linear Regression, Multivariate Polynomial Regression, Naives Bayes Classifier, Artificial Neural Network. It is observed that the proposed model designed using MARS technique achieved better results as compared to the other three techniques. This paper also focuses on the effectiveness of feature selection techniques to find a small subset of QoS parameters. These may be able to classify the web services with higher accuracy and also reduced the value of misclassification errors.
Description: Copyright belongs to proceeding publisher
URI: http://hdl.handle.net/2080/2402
Appears in Collections:Conference Papers

Files in This Item:
File Description SizeFormat 
QulaityAssesment_KumarL_2015.pdf116.33 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.