A learning approach to discovering web page semantic structures

Proceedings of the International Conference on Document Analysis and Recognition, ICDAR

Volumn 2005, Issue , 2005, Pages 1055-1059

  Feng, Junlan ^a   Haffner, Patrick ^a   Gilbert, Mazin ^a  

^a AT AND T LABS RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

SEMANTIC STRUCTURES; TEXT PARTITIONING; WEB NAVIGATION;

DATA MINING; INFORMATION ANALYSIS; SEARCH ENGINES; SEMANTICS; WEBSITES;

LEARNING SYSTEMS;

EID: 33947398913     PISSN: 15205363     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDAR.2005.19     Document Type: Conference Paper

References (14)

1. J. Feng, S. Bangalore, M. Rahim, "WebTalk: Mining websites for Automatically Building Dialog systems", Proc. Of IEEE ASRU 2003, St. Thomas, U. S. Virgin Islands, December 2003
2. Saikat Mukerjee, GuiZhen Yang, WenFang Tan, I.V.Ramakrishman, "Automatic Discovery of Semantic Structures in HTML Documents", ICDAR 2003
3. Y. Chen, W. Ma, H.Zhang, "Detecting Web Page Structure for Adaptive Viewing on Small Form Factor Devices", Proc. Of WWW 2003, May 20-24, 2003, Budapest, Hungary.
4. H. Davulcu, S. Koduri, S. Nagarajan, "DataRover, A Taxonomy Based Crawler for Automated Data Extraction from Data-Intensive Websites", WIDM'03, November 7-8, 2003, New Orleans, Louisiana, USA.
5. S. Yu, Yu.S. "Improve Pseudo-Relevance Feedback in Web Information Retrieval Using Web page Segmentation", WWW 2003
6. M. Hurst, "Layout and language: An efficient algorithm for text block detection based on spatial and linguistic evidence", Proc. Of Document Recognition and Retrieval VIII pages 56-67, 2001.
7. P. Haffner, G. Tur and J. Wright, "Optimizing SVMs for complex Call Classification" in ICASSP'03, Apr. 2003.
8. L. Eikvil, "Information Extraction from World Wide Web - A Survey", Rapport Nr. 945, July, 1999. ISBN 82-539-0429-0.
9. http://www.w3.org/html4/
10. http://www.w3.org/DOM/
11. C. Cortes and V. Vapnik, "Support-Vector Networks", Machine Learning, 20:273 - 297, 1995.
12. R.E. Schapire and Y. Singer, "Boostexter : A boosting-based system for text classification," Machine Learning, Vol. 39, no. 2/3, pp135-168, 2000.
13. C.Y.Chuang, M. Gertz, and N.Sundaresan. "Reverse engineering for web data: From visual to semantic structures", ICDE, 2002.
14. Y.Yang and H.Zhang. "HTML page analysis based on visual cues", ICDAR 2001.