Abstract
Browsing large web pages on small screens is still very inconvenient due to their limited display sizes. A straightforward solution is eliminating the annoying horizontal scrolling requirement, i.e. present all the contents into a single narrow column, usually named one-column view. It is implemented by deleting the layout that will cause horizontal scrolling. However, after deleting the layout structure, some structural information becomes unreadable, like data tables. In this paper, we propose an approach to improve web browsing on small devices by classifying HTML tables into data tables and layout tables. For data tables, we try to preserve the original structural information in the final presentation. Therefore, the browsing experience can be improved for the one-column view. Experimental results show that our approach can achieve a satisfactory performance.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Hurst, M.: Classifying Table Elements in HTML. In: Proc. WWW 2002, Honolulu, Hawaii, USA (2002)
Opera Small Screen Rendering, http://www.opera.com/products/smartphone/smallscreen/
Chen, Y., Ma, W.Y., Zhang, H.J.: Detecting Web Page Structure for Adaptive Viewing on Small Form Factor Devices. In: Proc. WWW 2003, Budapest, Hungary (2003)
Hori, M., Kondoh, G., Ono, K., Hirose, S., Singhal, S.: Annotation-based Web Content Transcoding. Computer Networks 33, 197–211 (2000)
Chang, C.C., Lin, C.J.: Libsvm: a library for support vector machines (2001), Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm
Zanibbi, R., Blostein, D., Cordy, J.R.: A Survey of Table Recognition: Models, Observations, Transformations, and Inferences. In: IJDAR (2004)
Wang, Y.L., Hu, J.Y.: Machine Learning Based Approach for Table Detection on the Web. In: Proc. WWW 2002, Honolulu, Hawaii, USA (2002)
Chen, H.H., Li, C.J., Tsai, J.H., Tsai, S.C.: Mining Tables from Large Scale HTML. In: Proc. ICCL 2000, Saarbrucken, Germany (2000)
Yoshida, M., Torisawa, K., Tsujii, J.: A Method to Integrate Tables of the World Wide Web. In: Proc. WDA 2001, Seattle, WA, USA, pp. 31–34 (2001)
Vapnik, V.N.: The Nature of Statistical Learning Theory. Springer, New York (1995)
Dempster, A.P., Laird, N.M., Rubin, D.B.: Maximum Likelihood from Incomplete Data via the EM Algorithm. Journal of the Royal Statistical Society B 39, 1–38 (1977)
Laurene, V.F.: Fundamentals of Neural Networks, 1st edn. Prentice-Hall, Englewood Cliffs (1994)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wang, C., Xie, X., Wang, W., Ma, WY. (2004). Improving Web Browsing on Small Devices Based on Table Classification. In: Aizawa, K., Nakamura, Y., Satoh, S. (eds) Advances in Multimedia Information Processing - PCM 2004. PCM 2004. Lecture Notes in Computer Science, vol 3332. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30542-2_12
Download citation
DOI: https://doi.org/10.1007/978-3-540-30542-2_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23977-2
Online ISBN: 978-3-540-30542-2
eBook Packages: Computer ScienceComputer Science (R0)