@article{645,
title = {A Web Metrics quality evaluation framework for e- commerce systems},
author = {Antonia Stefani and Vasileios Vasileiadis},
url = {http://daissy.eap.gr/wp-content/uploads/2015/03/2.A-Web-Metrics-quality-evaluation-framework.pdf},
year = {2013},
date = {2013-01-01},
journal = {Computer Standards and Interfaces Journal},
abstract = {E-commerce B2C systems are diverse and their quality is difficult to be measured without a concrete methodology. In this paper we present a B2C-specific quality evaluation framework for web metrics that helps understand what needs to be measured and how. The framework uses three dimensions based on end-user interaction categories, metrics internal specs and quality sub-characteristics as defined of ISO9126. Beginning from the existing large corpus of general-purpose web metrics, specific metrics used for quality evaluation of ecommerce systems are chosen and categorized. Analysis results are subjected to a data mining analysis in order to provide association rules between the various dimensions of the framework. Finally, an ontology that corresponds to the framework is developed to answer to complicated questions related to metrics use and to facilitate the production of new, user-defined meta-metrics .},
keywords = {E-commerce, evaluation framework, ISO 9126, Ontology, quality attributes, taxonomy, web metrics},
pubstate = {published},
tppubtype = {article}
}
E-commerce B2C systems are diverse and their quality is difficult to be measured without a concrete methodology. In this paper we present a B2C-specific quality evaluation framework for web metrics that helps understand what needs to be measured and how. The framework uses three dimensions based on end-user interaction categories, metrics internal specs and quality sub-characteristics as defined of ISO9126. Beginning from the existing large corpus of general-purpose web metrics, specific metrics used for quality evaluation of ecommerce systems are chosen and categorized. Analysis results are subjected to a data mining analysis in order to provide association rules between the various dimensions of the framework. Finally, an ontology that corresponds to the framework is developed to answer to complicated questions related to metrics use and to facilitate the production of new, user-defined meta-metrics .
