On finding templates on web collections

World Wide Web

Volumn 12, Issue 2, 2009, Pages 171-211

  Vieira, Karane ^a   da Costa Carvalho, André Luiz ^a   Berlt, Klessius ^a   de Moura, Edleno S ^a   da Silva, Altigran S ^a   Freire, Juliana ^b  

^a FEDERAL UNIVERSITY OF AMAZONAS   (Brazil)

^b University of Utah   (United States)

Author keywords

Tree mapping; Web IR; Web template detection

Indexed keywords

AUTOMATIC CATEGORIZATION; COMPUTATIONAL RESOURCES; CONTENT PROVIDERS; HTML PAGES; LINEAR COMPLEXITY; PROCESS INFORMATION; QUALITY OF RESULTS; TEMPLATE DETECTION; WEB COLLECTIONS; WEB IR; WEB PAGE;

ALGORITHMS; HTML; MAPPING; MARKUP LANGUAGES; SEARCH ENGINES; SIGNAL DETECTION; WEBSITES;

COMPUTATIONAL EFFICIENCY;

EID: 71349086902     PISSN: 1386145X     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11280-009-0059-3     Document Type: Article

References (26)

1. Bar-Yossef, Z., Rajagopalan, S.: Template detection via data mining and its applications. In: Proceedings of the International Conference on the World Wide Web, pp. 580-591 (2002).
2. Beszteri, I., Vuorimaa, P.: Vertical navigation of layout adapted web documents. World Wide Web 10(1), 1-35 (2007).
3. Chakrabarti, S., Joshi, M., Tawde, V.: Enhanced topic distillation using text, markup tags, and hy-perlinks. In: Proceedings the of ACM Conference on Research and Development in Information Retrieval, pp. 208-216 (2001).
4. Chakrabarti, D., Kumar, R., Punera, K.: Page-level template detection via isotonic smoothing. In: WWW'07: Proceedings of the 16th International Conference on World Wide Web, pp. 61-70. ACM, New York, NY, USA (2007).
5. Chen, W.: New algorithm for tree-to-tree correction problem. J. Algorithms 40, 135-158 (2001).
6. Chen, L., Ye, S., Li, X.: Template detection for large scale search engines. In: SAC'06: Proceedings of the 2006 ACM Symposium on Applied Computing, pp. 1094-1098. ACM, New York, NY, USA (2006).
7. Dalamagas, T., Cheng, T., Winkel, K. J., Sellis, T. K.: A methodology for clustering xml documents by structure. Inf. Syst. 31(3), 187-228 (2006).
8. de Castro 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 International Conference on the World Wide Web, pp. 502-511 (2004).
9. Debnath, S., Mitra, P., Giles, C.L.: Automatic extraction of informative blocks from webpages. In: ACM Symposium on Applied Computing, pp. 1722-1726 (2005).
10. Gibson, D., Punera, K., Tomkins, A.: The volume and evolution of web page templates. In: Proceedings of the International Conference on the World Wide Web-Poster Session, pp. 830-839. (2005).
11. Joshi, S., Agrawal, N., Krishnapuram, R., Negi, S.: A bag of paths model for measuring structural similarity in web documents. In: Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, pp. 577-582 (2003).
12. Khy, S., Ishikawa, Y., Kitagawa, H.: A novelty-based clustering method for on-line documents. World Wide Web 11(1), 1-37 (2008).
13. Lian, W., Cheung, D.W.L., Mamoulis, N., Yiu, S.M.: An efficient and scalable algorithm for clustering xml documents by structure. IEEE Trans. Knowl. Data Eng. 16(1), 82-96 (2004).
14. Macías, J.A.: Intelligent assistance in authoring dynamically generated web interfaces. World Wide Web 11(2), 253-286 (2008).
15. Nielsen, J.: User interface directions for the web. Commun. ACM 42(1), 65-72 (1999).
16. Nierman, A., Jagadish, H.V.: Evaluating structural similarity in XML documents. In: Proceedings of the International Workshop on the Web and Databases (2002).
17. Selkow, S.M.: The tree-to-tree editing problem. Inf. Process. Lett. 6, 184-186 (1977).
18. Song, R., Liu, H., Wen, J.R., Ma, W.Y.: Learning block importance models for web pages. In: Proceedings of the International Conference on the World Wide Web, pp. 203-211 (2004).
19. Tai, K.C.: The tree-to-tree correction problem. J. ACM 26(3), 422-433 (1979).
20. Valiente, G.: An efficient bottom-up distance between trees. In: Proceedings of the International Symposium on String Processing and Information Retrieval, pp. 212-219. IEEE Computer Science Press (2001).
21. Vieira, K., da Silva, A.S., Pinto, N., de Moura, E.S., Cavalcanti, J.M.B., Freire, J.: A fast and robust method for web page template detection and removal. In: Proceedings of the ACM International Conference on Information and Knowledge Management, Arlington, VA, USA, pp. 258-267 (2006).
22. Wang, J.T.L., Zhang, K.: Finding similar consensus between trees: an algorithm and a distance hierarchy. Pattern Recogn. 34, 127-137 (2001).
23. Yang, W.: Identifying syntactic differences between two programs. Softw. Pract. Exp. 21(7), 739-755 (1991).
24. Yi, L., Liu, B., Li, X.: Eliminating noisy information in web pages for data mining. In: Proceedings of the International ACM Conference on Knowledge Discovery and Data Mining, pp. 296-305 (2003).
25. Zhai, Y., Liu, B.: Extracting web data using instance-based learning. World Wide Web 10(2), 113-132 (2007).
26. Zhang, K., Statman, R., Shasha, D.: On the editing distance between unordered labeled trees. Inf. Process. Lett. 42(3), 133-139 (1992).