Towards language-independent web genre detection

ABSTRACT

The term web genre denotes the type of a given web resource, in contrast to the topic of its content. In this research, we focus on recognizing the web genres blog, wiki and forum. We present a set of features that exploit the hierarchical structure of the web page's HTML mark-up and thus, in contrast to related approaches, do not depend on a linguistic analysis of the page's content. Our results show that it is possible to achieve a very good accuracy for a fully language independent detection of structured web genres.

REFERENCES

• 1: R. Domínguez García, P. Scholl, D. Böhnstedt, C. Rensing, and R. Steinmetz. Automatic web genre classification using structural features. Technical Report KOM-TR-2008-06, Multimedia Kommunikation -- TU Darmstadt, Germany, July 2008.
• 2: S. Meyer zu Eissen and B. Stein. Genre classification of web pages -- user study and feasibility analysis. In KI 2004: Advances in Artificial Intelligence, volume 3238 of LNCS, pages 256--269. Springer Berlin / Heidelberg, 2004.
• 3: Davood Rafiei , Daniel L. Moise , Dabo Sun, Finding Syntactic Similarities Between XML Documents, Proceedings of the 17th International Conference on Database and Expert Systems Applications, p.512-516, September 04-08, 2006 [doi>10.1109/DEXA.2006.62]
• 4: M. Santini. Automatic Identification of Genre in Web Pages. PhD thesis, University of Brighton, January 2007.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.1 Content Analysis and Indexing
          Subjects: Abstracting methods

General Terms:
Algorithms

Keywords:
machine learning, structural features, web genres