Improving Accessibility of Transaction-centric Web Objects

Abstract

Advances in web technology have considerably widened the Web accessibility divide between sighted and blind users. This divide is especially acute when conducting online transactions, e.g., shopping, paying bills, making travel plans, etc. Such transactions span multiple web pages and require that users find clickable objects (e.g., "add-to-cart" button) which are essential for transaction progress. While this is fast and straightforward for sighted users, locating the clickable objects causes considerable strain for blind individuals using screenreading technology. Screen readers force users to listen to irrelevant information sequentially and provide no interface for identifying relevant clickable objects.This paper addresses the problem of making clickable objects readily accessible, which can substantially reduce the information overload that is otherwise experienced by blind users. A static knowledge base of keywords constructed from the captions of clickable objects does not provide enough learning capability for identifying clickable objects which do not have any captions (e.g., image buttons without alternative text). In this paper, we present an Information Retrieval based technique that uses the context of transactioncentric objects (e.g., "add-to-cart" and "checkout" buttons) to identify and classify them even when their captions are missing. In addition, the technique utilizes a reinforcement mechanism based on user feedback to accommodate previously unseen captions of objects as well as new categories of objects. We provide user study and experimental evidence of the effectiveness of our algorithm.

Mixture model based label association techniques for web accessibility

“…The FMM classifier showed an average accuracy of R=91%, P=93%, F1=92% in identification experiment, and R=89%, P=96%, F1=92% in classification. Even with the simplest formulation our results are comparable to [22]. Figure 11 Recall, Precision, and F-measure of identifying transaction elements on the shopping dataset Comparative Summary.…”

“…We recently proposed a solution to the 2 nd problem in [22]. The idea was to build a KB of transaction element classes such as an Add-To-Cart class, a Checkout class, and so on.…”

Usability Of An E-Commerce Website Using Information Mining and Artificial Intelligence

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“…So, usability of a site simply means whether a customer is finding a site to be useful or not. This article includes a study on website usability, trust evaluation and how to improve trust to improve the usability of a website [1].…”

Um auxílio à navegação acessível na web para usuários cegos

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