This document discusses a vision-based page segmentation algorithm called VIPS and its implementation and evaluation. The authors extend the VIPS algorithm to address its limitations handling HTML5, dynamic content, and lack of implementation details. Their open-source Java implementation improves on VIPS with an extended tag set, more visual attributes, and rules to handle invisible nodes. An online user survey evaluated the perceived success of the extended algorithm, finding higher ratings for more detailed segmentation levels. The authors conclude the extended algorithm resolves VIPS limitations and propose future work on dynamic content and other applications.

1. Introduction
VIPS Algorithm
Main Contribution
Evaluation
Conclusion
Vision Based Page Segmentation Algorithm:
Extended and Perceived Success
M. Elgin Akpnar1
Yeliz Ye³ilada2
1
elgin.akpinar@metu.edu.tr, Middle East Technical University, Ankara, Turkey
2
yyeliz@metu.edu.tr, Middle East Technical University
Northern Cyprus Campus, Kalkanl, Güzelyurt,
Mersin 10, Turkey
EMotions, 2013
M. Elgin Akpnar, Yeliz Ye³ilada

2. Introduction
VIPS Algorithm
Main Contribution
Evaluation
Conclusion
Outline
1 Introduction
2 VIPS Algorithm
3 Main Contribution
4 Evaluation
5 Conclusion
M. Elgin Akpnar, Yeliz Ye³ilada

3. Introduction
VIPS Algorithm
Main Contribution
Evaluation
Conclusion
Motivation
Related Work
Problem Denition
M. Elgin Akpnar, Yeliz Ye³ilada

4. Introduction
VIPS Algorithm
Main Contribution
Evaluation
Conclusion
Motivation
Related Work
Problem Deniton (cont.)
How to nd segments in a web page?
DOM Structure?
Predened page template?
Large pages?
How to maintain the solution?
Fast changing design trends?
New technologies?
Dierent application areas?
M. Elgin Akpnar, Yeliz Ye³ilada

5. Introduction
VIPS Algorithm
Main Contribution
Evaluation
Conclusion
Motivation
Related Work
Requirements
We need a segmentation method, which is;
Covering dierent design approaches
Compatible with current technologies
Modiable for dierent purposes
Easy to adopt to future technologies
Ecient and accurate
Platform independent
M. Elgin Akpnar, Yeliz Ye³ilada

6. Introduction
VIPS Algorithm
Main Contribution
Evaluation
Conclusion
Motivation
Related Work
Recent Application Fields
Mobile web access
[Yin Lee, 2004, Song et al., 2004, Hattori et al., 2007,
Ahmadi Kong, 2008, Hwang et al., 2003]
Web accessibility
[Yesilada et al., 2008, Asakawa Takagi, 2000,
Yesilada et al., 2004, Lunn et al., 2011, Mahmud et al., 2007]
Web page transcoding
[Hwang et al., 2003, Whang et al., 2001]
Information retrieval [Cai et al., 2003]
M. Elgin Akpnar, Yeliz Ye³ilada

7. Introduction
VIPS Algorithm
Main Contribution
Evaluation
Conclusion
Motivation
Related Work
Recent Approaches
Two types of approach:
Top-down page segmentation
Bottom-up page segmentation
Heuristic approach [Ahmadi Kong, 2008]
Machine learning [Baluja, 2006]
Visual attributes analysis [Cai et al., 2003]
M. Elgin Akpnar, Yeliz Ye³ilada

8. Introduction
VIPS Algorithm
Main Contribution
Evaluation
Conclusion
Motivation
Related Work
Importance of visual attributes
M. Elgin Akpnar, Yeliz Ye³ilada

9. Introduction
VIPS Algorithm
Main Contribution
Evaluation
Conclusion
VIPS Review
VIPS Limitations
VIPS Review
Label all nodes with respect to:
Their visibility
Line breaks they produce
Their children nodes
Three main parts:
1
Visual block extraction
2
Visual block separation
3
Content structure construction
Very eective for web page segmentation
M. Elgin Akpnar, Yeliz Ye³ilada

10. Introduction
VIPS Algorithm
Main Contribution
Evaluation
Conclusion
VIPS Review
VIPS Limitations
VIPS Review (cont.)
M. Elgin Akpnar, Yeliz Ye³ilada

11. Introduction
VIPS Algorithm
Main Contribution
Evaluation
Conclusion
VIPS Review
VIPS Limitations
Limitations and Extension Requirements
Corrective maintenance
Ambiguous denitions in rule set
Insucient visual rules
Adaptive maintenance
Incompatibility with HTML5
Problems with dynamic web content
Unprovided source code of implementation
M. Elgin Akpnar, Yeliz Ye³ilada

12. Introduction
VIPS Algorithm
Main Contribution
Evaluation
Conclusion
Implementation
Improvements
Implementation
Accessibility Tools Framework (ACTF)
(http://www.eclipse.org/actf/)
Java based implementation
Provided under Eclipse Public License
v1.0 so that anyone can benet and
contribute
Repository:
http://git.eclipse.org/c/actf/
org.eclipse.actf.examples.git
M. Elgin Akpnar, Yeliz Ye³ilada

13. Introduction
VIPS Algorithm
Main Contribution
Evaluation
Conclusion
Implementation
Improvements
Extended Tag Set
Classication of HTML5 tags
Further classication of line break tags based on the spaces
they produce around them
Example
a DIV node and a P node produce dierent size of spaces in visual
representation
M. Elgin Akpnar, Yeliz Ye³ilada

14. Introduction
VIPS Algorithm
Main Contribution
Evaluation
Conclusion
Implementation
Improvements
Extended Visual Attributes
Original algorithm covers;
Tag rules
Text and size rules
Color rules
Extended algorithm also covers;
Margin and padding styles
Float styles
M. Elgin Akpnar, Yeliz Ye³ilada

15. Introduction
VIPS Algorithm
Main Contribution
Evaluation
Conclusion
Implementation
Improvements
Invisible Nodes
Several ways of making a node invisible:
Setting display style to 'none'
Setting visibility style to 'hidden'
Setting absolute position of the node to the outside of the page
Setting text-indent style to a negative value
Leaf nodes without textual or graphical content
M. Elgin Akpnar, Yeliz Ye³ilada

16. Introduction
VIPS Algorithm
Main Contribution
Evaluation
Conclusion
Implementation
Improvements
Other Improvements
Clarication of poorly
dened rule precedences
Removal of undened
tresholds
M. Elgin Akpnar, Yeliz Ye³ilada

17. Introduction
VIPS Algorithm
Main Contribution
Evaluation
Conclusion
Evaluation
Results
Evaluation
Online survey based user evaluation
Nine randomly chosen web pages from a group of 30 pages
25 participants evaluated
Information sheet, demographics, rating and ranking levels of
segmentation
Investigated two main scientic questions:
What is the perceived success of our extended segmentation
algorithm?
Which level of segmentation is the most preferred?
M. Elgin Akpnar, Yeliz Ye³ilada

18. Introduction
VIPS Algorithm
Main Contribution
Evaluation
Conclusion
Evaluation
Results
Rating Results
Complexity Group Level 1 Level 2 Level 3 Level 4 Level 5
Low Comp. 47.2 % 58.4 % 66.4 % 70.45 % 72.22 %
Medium Comp. 42.4 % 52 % 66 % 73.6 % 74 %
High Comp. 40.8 % 51.6 % 62 % 68.4 % 76 %
M. Elgin Akpnar, Yeliz Ye³ilada

19. Introduction
VIPS Algorithm
Main Contribution
Evaluation
Conclusion
Evaluation
Results
Ranking Results
High Complexity Medium Complexity Low Complexity
Level No. B. W. B. W. B. W.
Level 5 38 4 1 2 6 31 3 1 2 11 17 1 1 1 6
Level 4 5 35 2 4 5 6 30 2 7 3 5 15 1 2 3
Level 3 2 5 36 5 3 5 5 33 2 3 1 4 13 5 3
Level 2 2 2 8 33 3 3 4 5 28 8 1 3 6 15 1
Level 1 2 2 4 7 32 3 6 7 9 23 2 3 5 3 12
M. Elgin Akpnar, Yeliz Ye³ilada

20. Introduction
VIPS Algorithm
Main Contribution
Evaluation
Conclusion
Conclusion
VIPS Limitations:
Ambiguous denitions in rule set
Insucient visual rules
Incompatibility with HTML5
Problems with dynamic web content
Source code of implementation is not
provided
Our contribution:
Open source, Java based implementation
Extended tag and rule sets
Resolved ambiguity problems
M. Elgin Akpnar, Yeliz Ye³ilada

21. Introduction
VIPS Algorithm
Main Contribution
Evaluation
Conclusion
Future Work
Dynamic content
Web page transcoding
Ontology based heuristic rule set
VIPS as a web service
Browser extensions
M. Elgin Akpnar, Yeliz Ye³ilada

22. Introduction
VIPS Algorithm
Main Contribution
Evaluation
Conclusion
Thank you for listening!
For further information
Contact: elgin.akpinar@metu.edu.tr
Project Page: http://emine.ncc.metu.edu.tr/
Thanks to
M. Elgin Akpnar, Yeliz Ye³ilada

23. References
Ahmadi, H. Kong, J. (2008).
Ecient web browsing on small screens.
In Proceedings of the working conference on Advanced visual
interfaces, AVI '08 (pp. 2330). New York, NY, USA: ACM.
Asakawa, C. Takagi, H. (2000).
Annotation-based transcoding for nonvisual web access.
In ASSETS'00 (pp. 172179).: ACM Press.
Baluja, S. (2006).
Browsing on small screens: recasting web-page segmentation
into an ecient machine learning framework.
In WWW '06: Proceedings of the 15th international conference
on World Wide Web (pp. 3342). New York, NY, USA: ACM.
M. Elgin Akpnar, Yeliz Ye³ilada

24. References
Cai, D., Yu, S., Wen, J.-R., Ma, W.-Y. (2003).
VIPS: a Vision Based Page Segmentation Algorithm.
Technical Report MSR-TR-2003-79, Microsoft Research.
Hattori, G., Hoashi, K., Matsumoto, K., Sugaya, F. (2007).
Robust web page segmentation for mobile terminal using
content-distances and page layout information.
In WWW '07: Proceedings of the 16th international conference
on World Wide Web (pp. 361370). New York, NY, USA: ACM
Press.
Hwang, Y., Kim, J., Seo, E. (2003).
Structure-aware web transcoding for mobile devices.
IEEE Internet Computing, 7(5), 1421.
M. Elgin Akpnar, Yeliz Ye³ilada

25. References
Lunn, D., Harper, S., Bechhofer, S. (2011).
Identifying behavioral strategies of visually impaired users to
improve access to web content.
ACM Trans. Access. Comput., 3(4), 13:113:35.
Mahmud, J. U., Borodin, Y., Ramakrishnan, I. V. (2007).
Csurf: a context-driven non-visual web-browser.
In Proceedings of the 16th international conference on World
Wide Web, WWW '07 (pp. 3140). New York, NY, USA: ACM.
Song, R., Liu, H., Wen, J.-R., Ma, W.-Y. (2004).
Learning block importance models for web pages.
In Proceedings of the 13th international conference on World
Wide Web, WWW '04 (pp. 203211). New York, NY, USA:
ACM.
M. Elgin Akpnar, Yeliz Ye³ilada

26. References
Whang, Y., Jung, C., Kim, J., Chung, S. (2001).
Webalchemist: A web transcoding system for mobile web
access in handheld devices.
In Optoelectronic and Wireless Data Management, Processing,
Storage, and Retrieval (pp. 102109).
Yesilada, Y., Chuter, A., Henry, S. L. (2008).
Shared Web Experiences: Barriers Common to Mobile Device
Users and People with Disabilities.
W3C.
.
M. Elgin Akpnar, Yeliz Ye³ilada

27. References
Yesilada, Y., Harper, S., Goble, C., Stevens, R. (2004).
Screen readers cannot see (ontology based semantic annotation
for visually impaired web travellers).
In Proceedings of the International Conference on Web
Engineering (ICWE) (pp. 445458).: Springer.
Yin, X. Lee, W. (2004).
Using link analysis to improve layout on mobile devices.
In Proceedings of the Thirteenth International World Wide
Web Conference (pp. 338344).
M. Elgin Akpnar, Yeliz Ye³ilada