APA 6th Edition Vidulin, V., Luštrek, M. i Gams, M. (2007). Training a Genre Classifier for Automatic Classification of Web Pages. Journal of computing and information technology, 15 (4), 305-311. https://doi.org/10.2498/cit.1001137
MLA 8th Edition Vidulin, Vedrana, et al. "Training a Genre Classifier for Automatic Classification of Web Pages." Journal of computing and information technology, vol. 15, br. 4, 2007, str. 305-311. https://doi.org/10.2498/cit.1001137. Citirano 23.01.2021.
Chicago 17th Edition Vidulin, Vedrana, Mitja Luštrek i Matjaž Gams. "Training a Genre Classifier for Automatic Classification of Web Pages." Journal of computing and information technology 15, br. 4 (2007): 305-311. https://doi.org/10.2498/cit.1001137
Harvard Vidulin, V., Luštrek, M., i Gams, M. (2007). 'Training a Genre Classifier for Automatic Classification of Web Pages', Journal of computing and information technology, 15(4), str. 305-311. https://doi.org/10.2498/cit.1001137
Vancouver Vidulin V, Luštrek M, Gams M. Training a Genre Classifier for Automatic Classification of Web Pages. Journal of computing and information technology [Internet]. 2007 [pristupljeno 23.01.2021.];15(4):305-311. https://doi.org/10.2498/cit.1001137
IEEE V. Vidulin, M. Luštrek i M. Gams, "Training a Genre Classifier for Automatic Classification of Web Pages", Journal of computing and information technology, vol.15, br. 4, str. 305-311, 2007. [Online]. https://doi.org/10.2498/cit.1001137
Sažetak This paper presents experiments on classifying web pages by genre. Firstly, a corpus of 1539 manually labeled web pages was prepared. Secondly, 502 genre features were selected based on the literature and the observation of the corpus. Thirdly, these features were extracted from the corpus to obtain a data set. Finally, two machine learning algorithms, one for induction of decision trees (J48) and one ensemble algorithm (bagging), were trained and tested on the data set. The ensemble algorithm achieved on average 17% better precision and 1.6% better accuracy, but slightly worse recall; F-measure did not vary significantly. The results indicate that classification by genre could be a useful addition to search engines.