Abstract
Web page classification has been extensively researched, using different types of features that are extracted either from the page content, the page structure or from other pages that link to that page. Using features from the page itself implies having to download it before its classification. We present an experiment to proof that URL tokens contain information enough to extract features to classify web pages. A classifier based on these features is able to classify a web page without having to download it previously, avoiding unnecessary downloads.
Supported by the European Commission (FEDER), the Spanish and the Andalusian R&D&I programmes (grants TIN2007-64119, P07-TIC-2602, P08-TIC-4100, TIN2008- 04718-E, TIN2010-21744, TIN2010-09809-E, TIN2010-10811-E, and TIN2010-09988-E).
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
Arasu, A., Garcia-Molina, H.: Extracting structured data from web pages. In: SIGMOD, pp. 337–348 (2003)
Bar-Yossef, Z., Rajagopalan, S.: Template detection via data mining and its applications. In: WWW, pp. 580–591 (2002)
Baykan, E., Henzinger, M.R., Marian, L., Weber, I.: Purely URL-based topic classification. In: WWW, pp. 1109–1110 (2009)
Baykan, E., Henzinger, M.R., Weber, I.: Web page language identification based on URLs. PVLDB 1(1), 176–187 (2008)
Blanco, L., Crescenzi, V., Merialdo, P.: Structure and semantics of Data-IntensiveWeb pages: An experimental study on their relationships. J. UCS 14(11), 1877–1892 (2008)
Blanco, L., Dalvi, N., Machanavajjhala, A.: Highly efficient algorithms for structural clustering of large websites. In: WWW, pp. 437–446. ACM, New York (2011)
Cohen, W.W.: Improving a page classifier with anchor extraction and link analysis. In: NIPS, pp. 1481–1488 (2002)
Fürnkranz, J.: Hyperlink ensembles: a case study in hypertext classification. Information Fusion 3(4), 299–312 (2002)
Hernández, I., Sleiman, H.A., Ruiz, D., Corchuelo, R.: A Conceptual Framework for Efficient Web Crawling in Virtual Integration Contexts. In: Gong, Z., Luo, X., Chen, J., Lei, J., Wang, F.L. (eds.) WISM 2011, Part II. LNCS, vol. 6988, pp. 282–291. Springer, Heidelberg (2011)
Hernández, I., Rivero, C.R., Ruiz, D., Corchuelo, R.: A Tool for Link-Based Web Page Classification. In: Lozano, J.A., Gámez, J.A., Moreno, J.A. (eds.) CAEPIA 2011. LNCS, vol. 7023, pp. 443–452. Springer, Heidelberg (2011)
Hotho, A., Maedche, A., Staab, S.: Ontology-based text document clustering. KI 16(4), 48–54 (2002)
Kan, M.-Y., Thi, H.O.N.: Fast webpage classification using URL features. In: CIKM, pp. 325–326 (2005)
Pierre, J.M.: On the automated classification of web sites. CoRR, cs.IR/0102002 (2001)
Selamat, A., Omatu, S.: Web page feature selection and classification using neural networks. Inf. Sci. 158, 69–88 (2004)
Vidal, M.L.A., da Silva, A.S., de Moura, E.S., Cavalcanti, J.M.B.: Structure-based crawling in the hidden web. J. UCS 14(11), 1857–1876 (2008)
Zhu, M., Hu, W., Wu, O., Li, X., Zhang, X.: User oriented link function classification. In: WWW, pp. 1191–1192 (2008)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hernández, I., Rivero, C.R., Ruiz, D., Arjona, J.L. (2012). An Experiment to Test URL Features for Web Page Classification. In: RodrÃguez, J., Pérez, J., Golinska, P., Giroux, S., Corchuelo, R. (eds) Trends in Practical Applications of Agents and Multiagent Systems. Advances in Intelligent and Soft Computing, vol 157. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28795-4_13
Download citation
DOI: https://doi.org/10.1007/978-3-642-28795-4_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28794-7
Online ISBN: 978-3-642-28795-4
eBook Packages: EngineeringEngineering (R0)