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An Intelligent Method to Assess Webpage Quality using Extreme Learning Machine


B. Jayanthi, P. Krishnakumari


Vol. 16  No. 9  pp. 81-85


The rapid growth of the Internet as an environment for information exchange and the lack of enforceable standards regarding the information it contains numerous information quality problems. Website quality is dependent on the quality of the software. In the early years, quality of software provided effective support to develop the websites’ performance. However, in the website application of new discipline quality is the major challenging process. There is an increase in the web technology, so there is a need for factors access which is associated with success of website increases as well. Many of the existing website evaluation methods and criteria for evaluating website quality are unable to sufficiently assess the performance and quality of a website, and most of them focus on usability and accessibility. This work proposed an intelligent algorithm based on Extreme Learning Machine (ELM) for evaluating the website quality with respect to the service type which it offers. It is able to evaluate a website which has “best” or “worst” quality by type or by pasting a URL into the text box.


Web Page Quality, Support Vector Machine, Extreme Learning Machine, Intelligent Webpage Quality Assessment