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An important aspect of making the Web accessible to blind users is ensuring that all important web page elements such as links, clickable buttons, and form fields have explicitly assigned labels. Properly labeled content is then correctly read out by screen readers, a dominant assistive technology used by blind users. In particular, improperly labeled form fields can critically impede online transactions such as shopping, paying bills, etc. with screen readers. Very often labels are not associated with form fields or are missing altogether, making form filling a challenge for blind users. Algorithms for associating a form element with one of several candidate labels in its vicinity must cope with the variability of the element's features including label's location relative to the element, distance to the element, etc. Probabilistic models provide a natural machinery to reason with such uncertainties. In this paper we present a Finite Mixture Model (FMM) formulation of the label association problem. The variability of feature values are captured in the FMM by a mixture of random variables that are drawn from parameterized distributions. Then, the most likely label to be paired with a form element is computed by maximizing the log-likelihood of the feature data using the Expectation-Maximization algorithm. We also adapt the FMM approach for two related problems: assigning labels (from an external Knowledge Base) to form elements that have no candidate labels in their vicinity and for quickly identifying clickable elements such as add-to-cart, checkout, etc., used in online transactions even when these elements do not have textual captions (e.g., image buttons w/o alternative text). We provide a quantitative evaluation of our techniques, as well as a user study with two blind subjects who used an aural web browser implementing our approach.

We present a new web automation system that allows users to create a smart bookmark, consisting of a starting URL plus a script of commands that returns to a particular web page or state of a web application. A smart bookmark can be requested for any page, and the necessary commands are automatically extracted from the user's interaction history. Unlike other web macro recorders, which require the user to start recording before navigating to the desired page, smart bookmarks are generated retroactively, after the user has already reached a page, and the starting point of the macro is found automatically. Smart bookmarks have a rich graphical visualization that combines textual commands, web page screenshots, and animations to explain what the bookmark does. A bookmark's script consists of keyword commands, interpreted without strict reliance on syntax, allowing bookmarks to be easily edited and shared.

We present a new server-side architecture that enables rapid prototyping and deployment of mobile web applications created from existing web sites. Key to this architecture is a remote control metaphor in which the mobile device controls a fully functional browser that is embedded within a proxy server. Content is clipped from the proxy browser, transformed if necessary, and then sent to the mobile device as a typical web page. Users' interactions with that content on the mobile device control the next steps of the proxy browser. We have found this approach to work well for creating mobile sites from a variety of existing sites, including those that use dynamic HTML and AJAX technologies. We have conducted a small user study to evaluate our model and API with experienced web programmers.