Eliminating noisy information in Web pages for data mining
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Towards the creation of accessibility agents for non-visual navigation of the web
CUU '03 Proceedings of the 2003 conference on Universal usability
Accessibility designer: visualizing usability for the blind
Assets '04 Proceedings of the 6th international ACM SIGACCESS conference on Computers and accessibility
OntoMiner: Bootstrapping and Populating Ontologies from Domain-Specific Web Sites
IEEE Intelligent Systems
WebInSight:: making web images accessible
Proceedings of the 8th international ACM SIGACCESS conference on Computers and accessibility
Combating information overload in non-visual web access using context
Proceedings of the 12th international conference on Intelligent user interfaces
Analysis of navigability of Web applications for improving blind usability
ACM Transactions on Computer-Human Interaction (TOCHI)
CoScripter: automating & sharing how-to knowledge in the enterprise
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Hunting for headings: sighted labeling vs. automatic classification of headings
Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility
An evaluation of web accessibility metrics based on their attributes
Proceedings of the 26th annual ACM international conference on Design of communication
Trailblazer: enabling blind users to blaze trails through the web
Proceedings of the 14th international conference on Intelligent user interfaces
Bridging the Web Accessibility Divide
Electronic Notes in Theoretical Computer Science (ENTCS)
IR interface for contrasting multiple news sites
AIRS'08 Proceedings of the 4th Asia information retrieval conference on Information retrieval technology
Interpreting results from large scale automatic evaluation of web accessibility
ICCHP'06 Proceedings of the 10th international conference on Computers Helping People with Special Needs
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In this paper we present an approach to assessing the accessibility of Web pages, based on machine learning techniques. We are interested in the question of whether there are structural and textual features of Web pages, independent of explicit accessibility concerns, that nevertheless influence their usability for people with vision impairment. We describe three datasets, each containing a set of features corresponding to Web pages that are "Accessible" or "Inaccessible". Three classifiers are used to predict the category of these Web pages. Preliminary results are promising; they suggest the possibility of automated classification of Web pages with respect to accessibility.