Web Mediators for Accessible Browsing

  • Benjamin N. Waber
  • John J. Magee
  • Margrit Betke
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4397)


We present a highly accurate method for classifying web pages based on link percentage, which is the percentage of text characters that are parts of links normalized by the number of all text characters on a web page. We also present a novel link grouping algorithm using agglomerative hierarchical clustering that groups links in the same spatial neighborhood together while preserving link structure. Grouping allows users with severe disabilities to use a scan-based mechanism to tab through a web page and select items. In experiments, we saw up to a 40-fold reduction in the number of commands needed to click on a link with a scan-based interface. Our classification method consistently outperformed a baseline classifier even when using minimal data to generate article and index clusters, and achieved classification accuracy of 94.0% on web sites with well-formed or slightly malformed HTML, compared with 80.1% accuracy for the baseline classifier.


Web mediators link grouping web page classification  k-means clustering 


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  1. 1.
    Document object model (dom) level 1 specificiation version 1.0. W3C Recommendation (1998)Google Scholar
  2. 2.
    Betke, M., Gips, J., Fleming, P.: The Camera Mouse: Visual tracking of body features to provide computer access for people with severe disabilities. IEEE Transactions on Neural Systems and Rehabilitation Engineering 10(1), 1–10 (2002)CrossRefGoogle Scholar
  3. 3.
    Bharat, K., Chang, B., Henzinger, M., Ruhl, M.: Who links to whom: Mining linkage between web sites. In: International Conference on Data Mining (ICDM), pp. 51–58 (2001)Google Scholar
  4. 4.
    Buyukkokten, O., Garcia-Molina, H., Paepcke, A.: Seeing the whole in parts: text summarization for web browsing on handheld devices. In: Proceedings of the 10th International World Wide Web Conference (WWW), Hong Kong, pp. 652–662 (2001)Google Scholar
  5. 5.
    Chen, Y., Ma, W.-Y., Zhang, H.-J.: Detecting web page structure for adaptive viewing on small form factor devices. In: Proceedings of the 12th International World Wide Web Conference (WWW), Budapest, Hungary, pp. 225–233 (2003)Google Scholar
  6. 6.
    Chi, E.H.-H., Rosien, A., Supattanasiri, G., Williams, A., Royer, C., Chow, C., Robles, E., Dalal, B., Chen, J., Cousins, S.: The bloodhound project: automating discovery of web usability issues using the infoscent simulator. In: Computer-Human Interaction 2003 Conference on Human Factors in Computing Systems (CHI), pp. 505–512 (2003)Google Scholar
  7. 7.
    Cimiano, P., Handschuh, S., Staab, S.: Towards the self-annotating web. In: Proceedings of the 13th International World Wide Web Conference (WWW), New York City, pp. 462–471 (2004)Google Scholar
  8. 8.
    Cimiano, P., Ladwig, G., Staab, S.: Gimme’ the context: Context-driven automatic semantic annotation with C-PANKOW. In: Proceedings of the 14th International World Wide Web Conference (WWW), Chiba, Japan, pp. 332–341 (2005)Google Scholar
  9. 9.
    DiMattia, P., Curran, F.X., Gips, J.: An Eye Control Teaching Device for Students without Language Expressive Capacity – EagleEyes. The Edwin Mellen Press, Lewiston (2001)Google Scholar
  10. 10.
    Duda, R., Hart, P., Stork, D.: Pattern Classification. Wiley-Interscience, Chichester (2001)zbMATHGoogle Scholar
  11. 11.
    Fogaras, D., Rácz, B.: Scaling link-based similarity search. In: Proceedings of the 14th International World Wide Web Conference (WWW), Chiba, Japan, pp. 641–650 (2005)Google Scholar
  12. 12.
    Gupta, S., Kaiser, G.: Extracting content from accessible web pages. In: Proceedings of the 14th International World Wide Web Conference (WWW), Chiba, Japan, pp. 26–30 (2005)Google Scholar
  13. 13.
    Gupta, S., Kaiser, G., Stolfo, S.: Extracting context to improve accuracy for html content extraction. In: Proceedings of the 14th International World Wide Web Conference (WWW), Chiba, Japan, pp. 1114–1115 (2005)Google Scholar
  14. 14.
    Hornbæk, K., Bederson, B.B., Plaisant, C.: Navigation patterns and usability of zoomable user interfaces with and without an overview. ACM Transactions on Human-Computer Interaction 9(4), 362–389 (2002)CrossRefGoogle Scholar
  15. 15.
    Kim, J.W., Candan, K.S., Dönderler, M.E.: Topic segmentation of message hierarchies for indexing and navigation support. In: Proceedings of the 14th International World Wide Web Conference (WWW), Chiba, Japan, pp. 322–331 (2005)Google Scholar
  16. 16.
    Larson, H., Gips, J.: A web browser for people with quadriplegia. In: 10th International Conference on Human-Computer Interaction, Crete, Greece (2003)Google Scholar
  17. 17.
    Leporini, B., Paternò, F.: Increasing usability when interacting through screen readers. Universal Access in the Information Society 3(1), 57–70 (2004)CrossRefGoogle Scholar
  18. 18.
    Milic-Frayling, N., Jones, R., Rodden, K., Smyth, G., Blackwell, A., Sommerer, R.: SmartBack: Supporting users in back navigation. In: Proceedings of the 13th International World Wide Web Conference (WWW), New York City, pp. 63–71 (2004)Google Scholar
  19. 19.
    Montogmery, A., Faloutsos, C.: Indentifying web browsing trends and patterns. Computer, pp. 94–95 (2001)Google Scholar
  20. 20.
    Paquette, M., Betke, M., Magee, J.: IWeb Explorer: A web browser designed for use with an eye controlled mouse device. Boston University Computer Science MA Thesis Report (2005)Google Scholar
  21. 21.
    Parmanto, B., Ferrydiansyah, R., Saptono, A., Song, L., Sugiantara, I.W., Hackett, S.: AcceSS: Accessibility through simplification & summarization. In: Proceedings of the Second International Cross-Disciplinary Workshop on Web Accessibility (W4A2005), Chiba, Japan, pp. 18–25 (2005)Google Scholar
  22. 22.
    Pitkow, J., Schutze, H., Cass, T., Cooley, R., Turnbull, D., Edmonds, A., Adar, E., Breuel, T.: Personalized search. Commun. ACM 45(9), 50–55 (2002)CrossRefGoogle Scholar
  23. 23.
    Reis, D., Golgher, P.B., da Silva, A.S., Laender, A.H.F.: Automatic web news extraction using tree edit distance. In: Proceedings of the 13th International World Wide Web Conference (WWW), New York City, pp. 502–511 (2004)Google Scholar
  24. 24.
    Stephanidis, C., Paramythis, A., Karagiannidis, C., Savidis, A.: Supporting Interface Adaptation: The AVANTI WebBrowser. In: Proceedings of the 3rd ERCIM Workshop on User Interfaces for All, Obernai, France (1997)Google Scholar
  25. 25.
    Sullivan, T., Matson, R.: Barriers to use: Usability and content accessibility on the web’s most popular sites. In: Proceedings of the 2000 Conference on Universal Usability, Arlington, Virginia, USA, pp. 139–144 (2000)Google Scholar
  26. 26.
    Winograd, T.: Architectures for context. Human-Computer Interaction 10(24), 401–419 (2001)CrossRefGoogle Scholar
  27. 27.
    Yi, L., Liu, B., Li, X.: Eliminating noisy information in web pages for data mining. In: KDD ’03: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining, Washington, D.C., USA, pp. 296–305. ACM, New York (2003)CrossRefGoogle Scholar

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Benjamin N. Waber
    • 1
  • John J. Magee
    • 1
  • Margrit Betke
    • 1
  1. 1.Computer Science Department, Boston University, 111 Cummington St. Boston, MAUSA

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