Text classification, whether by topic or genre, is an important task that contributes to text extraction, retrieval, summarization and question answering. In this paper we present a new pairwise ensemble approach, which uses pairwise Support Vector Machine (SVM) classifiers as base classifiers and “input-dependent latent variable” method for model combination. This new approach better captures ...

This study aims to analyze the scientific approach and method of learning show results in genre-based Indonesian language learning. used a qualitative approach. The data were collected from three sources: literature review, student outcomes, questionnaire results. Data on students’ outcomes views explicitly taken two groups. first group consisted 113 respondents who asked construct literary tex...

Webpages are mainly distinguished by their topic (e.g., politics, sports etc.) and genre (e.g., blogs, homepages, e-shops, etc.). Automatic detection of webpage genre could considerably enhance the ability of modern search engines to focus on the requirements of the user’s information need. In this paper, we present an approach to webpage genre detection based on a fully-automated extraction of...

Research on teaching writing in Arabic as a less commonly taught language is still in its infancy. Motivated by the dearth of research on the integration of the genre-based approach into teaching writing in Arabic and the absence of such an approach, this paper proposes a genre-based framework for teaching writing in Arabic. Building on conclusions drawn from recent research, it proposes four s...

Classification and abstraction of narrative content is a problem that spans several domains and disciplines ranging from Film Studies and Narratology to Adaptive Hypermedia and Computational Preference Modeling. Applications for automatic recognition and classification of narrative content range from commercial recommendation systems to interactive digital storytelling (IDS) systems. The notion...