Assessing the Traffic Ranking of Websites with Artificial Neural Network

D.-M. Yeh, C.-C. Li, and S.-L. Chu (Taiwan)


Web technology, Website evaluation, Artificial Neural Network, usability, Web metrics


The website evaluation is an essential work in the time when the popularity and the ubiquity of the World Wide Web demonstrate its role in our everyday lives. In the past, researchers evaluated the websites by manpower and heuristic rules. In this study, we propose to assess the traffic ranking of web sites based on certain quantifiable criteria and the application of Artificial Neural Network (ANN). We use ANN to learn the rules of popular websites and compare the results with actualities. Then we infer the possible reasons of popularity from the learning results and re-evaluate the previous evaluation criteria. We hope that this research could present the current development of website evaluation, offer insights to website designers and web masters.

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