Combining labeled and unlabeled data with co-training
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Web classification using support vector machine
Proceedings of the 4th international workshop on Web information and data management
Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Labeling images with a computer game
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Improving accessibility of the web with a computer game
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
WebInSight:: making web images accessible
Proceedings of the 8th international ACM SIGACCESS conference on Computers and accessibility
Accessmonkey: a collaborative scripting framework for web users and developers
W4A '07 Proceedings of the 2007 international cross-disciplinary conference on Web accessibility (W4A)
Proceedings of the 27th ACM international conference on Design of communication
TextSL: a command-based virtual world interface for the visually impaired
Proceedings of the 11th international ACM SIGACCESS conference on Computers and accessibility
Seek-n-Tag: a game for labeling and classifying virtual world objects
Proceedings of Graphics Interface 2010
Automatic checking of alternative texts on web pages
ICCHP'10 Proceedings of the 12th international conference on Computers helping people with special needs: Part I
Back navigation shortcuts for screen reader users
Proceedings of the 14th international ACM SIGACCESS conference on Computers and accessibility
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The lack of appropriate alternative text for web images remains a problem for blind users and others accessing the web with non-visual interfaces. The content contained within web images is vital for understanding many web sites but the majority are assigned either inaccurate alternative text or none at all. The capability to automatically judge the quality of alternative text has the promise to dramatically improve the accessibility of the web by bringing intelligence to three categories of interfaces: tools that help web authors verify that they have provided adequate alternative text for web images, systems that automatically produce and insert alternative text for web images, and screen reading software. In this paper we describe a classifier capable of measuring the quality of alternative text given only a few labeled training examples by automatically considering the image context.