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SADIe - Exposing Implicit Information to Improve Accessibility
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SADIe - Exposing Implicit Information to Improve Accessibility

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The World Wide Web (Web) is a visually complex, multimedia system that can be inaccessible to people with visual impairments. SADIe addresses this problem by using Semantic Web technologies to …

The World Wide Web (Web) is a visually complex, multimedia system that can be inaccessible to people with visual impairments. SADIe addresses this problem by using Semantic Web technologies to explicate implicit visual structures through a combination of an upper and lower ontology. This is then used to apply accurate transcoding to a range of Websites. To gauge the effectiveness of SADIe's transcoding capability, a user was presented with a series of Web pages, a sample of which had been adapted using SADIe. The results showed that providing answers to fact based questions could be achieved more quickly when information was exposed via SADIe's transcoding. The data obtained during the experiment was analysed with a randomization test to show that the results were statistically significant for a single user.

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  • 1. SADIe Exposing Implicit Information to Improve Accessibility Darren Lunn School of Computer Science
  • 2. The Web…
    • Designed with a focus on presenting information in a visual manner
      • Images
      • Columned Layout
      • Chunks
    • Some knowledge is only available implicitly from how the page looks
  • 3. Implicit Knowledge = Advertisement = Banner = Main Content = Menu
  • 4. Assistive Technologies
    • Traversal of content is in a serial “top-to-bottom”, “left-to-right” manner.
    • Important information may not be encountered until later on.
    • Also, information such as menus or navigation may be repeated for every page on a site
      • This can prove tiresome if the user has to wait for the reader to read the menu each time a new page is visited.
  • 5. Transcoding
    • Rules / Patterns
      • Can Adapt a large number of pages
      • Can Suffer from Reduced Accuracy Issues
    • Annotation
      • Accurate
      • Time Consuming As Every Page Is Annotated
  • 6. SADIe Approach
    • The visual rendering of a Web element informs the user of its purpose
    • The CSS defines the visual rendering
    • Identifying the purpose of a CSS definition implicitly identifies the purpose of the Web element
    • A single CSS definition is applied to every page within the Website
  • 7. SADIe Functionality
    • Defluff : Removes any element that is considered unnecessary
    • Reorder : Rearranges the page by putting important information near the top
    • Menu : Exposes the menu at the very top for immediate access
  • 8. Original CNN
  • 9. SADIefied CNN
  • 10. Evaluation
    • We want to show that using SADIe decreases the time it takes to find information on the page
    • Only a small number of users available for evaluation
    • Use Randomization Testing
      • Data analysis techniques suitable for small numbers of users
  • 11. A-B-A Reversal Method
    • Two Conditions; A and B
      • Condition A: Unmodified Pages
      • Condition B: Pages Adapted With SADIe
    • Present the participant with Condition A tasks
    • At a random point, switch to Condition B tasks
    • At a second random point, revert back to Condition A tasks
    • This reduces the influence of external factors on the results
      • Participant has time to relax
      • Participant becomes familiar with the task at hand
  • 12. Evaluation Method
    • 20 pages that had similar content that was predominantly text based
      • News e.g. CNN, BBC, New York Times…
      • Blogs e.g. Blogger, Xanga…
    • Asked the user to find facts that were as similar for each page possible
      • Eg for news sites “What is the headline of the news story?”
    • The user was presented with a page one at a time, some of which were SADIefied (Condition B)
    • We timed how long it took the user to answer the question
  • 13. Evaluation Results
  • 14. Evaluation Results
    • So far we have evaluated SADIe with a single user
    • Results are encouraging and are significant using Randomization Testing…
    • … but are currently recruiting more users to support our results.
  • 15. Further Work
    • This is still preliminary work, and much remains to do
    • Extend and Enhance the Transformations
    • (Semi)-Automation of CSS classification
    • More User Evaluations
  • 16. Conclusions
    • Browsing the Web can be difficult for those who are visually impaired
    • SADIe can adapt Web pages by using rendering information extracted from the CSS
    • Initial evaluation results are promising and show that SADIe can help visually impaired users reach content more quickly
    • More work still needs to be done
  • 17. Questions? http://hcw.cs.manchester.ac.uk/research/sadie