Naslov
Web Genre Classification via Hierarchical Multi- label Classification

Autori
Madjarov, Gjorgji ; Vidulin, Vedrana ; Dimitrovski, Ivica ; Kocev, Dragi

Izvornik
Intelligent Data Engineering and Automated Learning – IDEAL 2015, Lecture notes in computer science (0302-9743) LNCS 9375 (2015); 9-17

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Web genre classification, Hierarchy construction, Hierarchical multi-label classification

Sažetak
The increase of the number of web pages prompts for improvement of the search engines. One such improvement can be by specifying the desired web genre of the result web pages. This opens the need for web genre prediction based on the information on the web page. Typically, this task is addressed as multi-class classification, with some recent studies advocating the use of multi-label classification. In this paper, we propose to exploit the web genres labels by constructing a hierarchy of web genres and then use methods for hierarchical multi-label classification to boost the predictive performance. We use two methods for hierarchy construction: expert-based and data- driven. The evaluation on a benchmark dataset (20- Genre collection corpus) reveals that using a hierarchy of web genres significantly improves the predictive performance of the classifiers and that the data-driven hierarchy yields similar performance as the expert-driven with the added value that it was obtained automatically and fast.

Izvorni jezik
Engleski

POVEZANOST RADA