Content-related metadata plays an important role in the effort of developing intelligent web applications. One of the most established form of providing content-related metadata is the assignment of web-pages to content categories. We describe the Spectacle system for classifying individual web pages on the basis of their syntactic structure. This classification requires the spe-cification of classification rules associating common pa-ge structures with predefined classes. In this paper, we propose an approach for the automatic acquisition of these classification rules using techniques from inducti-ve logic programming and describe experiments in ap-plying the approach to an existing web-based informa-tion system.
CITATION STYLE
Stuckenschmidt, H., Hartmann, J., & van Harmelen, F. (2002). Learning Structural Classification Rules for Web-page Categorization. In S. Haller & G. Simmons (Eds.), Proceedings of the Fifteenth International FLAIRS conference (pp. 440–444). Retrieved from http://www.aaai.org/Papers/FLAIRS/2002/FLAIRS02-086.pdf
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