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Web Genre Classification via Hierarchical Multi- label Classification (CROSBI ID 320969)

Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija

Madjarov, Gjorgji ; Vidulin, Vedrana ; Dimitrovski, Ivica ; Kocev, Dragi Web Genre Classification via Hierarchical Multi- label Classification // Lecture notes in computer science, LNCS 9375 (2015), 9-17. doi: 10.1007/978-3-319-24834-9_2

Podaci o odgovornosti

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

engleski

Web Genre Classification via Hierarchical Multi- label Classification

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.

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

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Podaci o izdanju

LNCS 9375

2015.

9-17

objavljeno

0302-9743

10.1007/978-3-319-24834-9_2

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