This work addresses the problem of genre classification of text and speech transcripts, with the goal of handling genres not seen in training. Two frameworks employing different statistics on word/POS histograms with a PCA transform are examined: a single model for each genre and a factored representation of genre. The impact of the two frameworks on the classification of training-matched and n...

Domain adaptation is an active field of research in statistical machine translation (SMT), but so far most work has ignored the distinction between the topic and genre of documents. In this paper we quantify and disentangle the impact of genre and topic differences on translation quality by introducing a new data set that has controlled topic and genre distributions. In addition, we perform a d...

In this paper, we report on a preliminary study we carried out for identifying patterns that characterize the genre type of Greek texts. In the course of our study, we address four distinct genre types, we record their observable stylistic elements and we indicate their exploitation for automatic genre-based document classification. The findings of our study demonstrate that texts contain lexic...

In this chapter, we discuss different options for using genre-related information in Web search. We conduct an experiment on merging genre-related and text-relevance rankings using a reference Web collection. A method for automatic extraction of formality score akin to readability score using canonical discriminant analysis applied to a sample of genres with decreasing formality is proposed. Ef...

This paper proposes shot genre classification from MPEG compressed movies, as one of the high-level indexing methods for audio-visual contents. Through statistical analysis of low-level and mid-level audio-visual features on compressed domain, the proposed method can achieve subjectively accurate shot classification within the movies into predefined genre set, which can be applied to various co...

This paper presents an automatic genre classification model that implements a flexible classification scheme, i.e. a scheme capable of performing zero-, oneor multi-genre assignment. I suggest that this scheme is more appropriate for genres on the web, because many web pages have often more than one genre or none at all. The model that I propose relies on the distinction between the concepts of...