Exploring the Use of Linguistic Features in Domain and Genre Classification

The central questions are: How useful is information about part-of-speech frequency for text categorisation? Is it feasible to limit word features to content words for text classifications? This is examined for 5 domain and 4 genre classification tasks using LIMAS, the German equivalent of the Brown corpus. Because LIMAS is too heterogeneous, neither question can be answered reliably for any of the tasks. However, the results suggest that both questions have to be examined separately for each task at hand, because in some cases, the additional information can indeed improve performance. 1 I n t r o d u c t i o n The greater the amounts of text people can access and have to process, the more important efficient methods for text categorisation become. So far, most research has concentrated on contentbased categories. But determining the g e n r e of a text can also be very important , for example when having to distinguish an EU press release on the introduction of the euro from a newspaper commentary on the same topic. The results of e.g. (Lewis, 1992; Yang and Pedersen, 1997) indicate that for good content classification, we basically need a vector which contains the most relevant words of the text. Using n-grams hardly yields significant improvements, because the dimension of the document representation space increases exponentially. But do wordbased vectors also work well for genre detection? Or do we need additional linguistically motivated features to capture the different styles of writing associated with different genres? In this paper, we present a pilot study based on a set of easily computable linguistic features, namely the frequency of part-of-speech (POS) tags, and a corpus of German, LIMAS (Glas, 1975), which contains a wide range of different genres. LIMAS is described briefly in Sac. 3, while sections 2 and 4 motivate the choice of features. The text categorisation experiments are described in Sec. 5. 2 L i n g u i s t i c C u e s to G e n r e 2.1 W h a t is genre? The term "genre" is more frequent in philology and media studies than in mainst ream linguistics (Swales, 1990, p.38). When it is not used synonymously with the terms "register" or "style", genre is defined on the basis of non-linguistic criteria. For example, (Biber, 1988) characterises genres in terms of author/speaker purpose, while text types classify texts on the basis of text-internal criteria. Swales phrases this more precisely: Genres are collections of communicative events with shared communicative purposes which can vary in their prototypicality. These communicative purposes are determined by the discourse communi ty which produces and reads texts belonging to a genre. But how can we extract its communicative purpose from a given text? First of all, we need to define the genres we want to detect. The definitions which were used in this study are summarised in section 3.1. If we assume that the culture-specific conventions which form the basis for assigning a given text to a certain genre are reflected in the style of the text, and if tha t style can be characterised quantitatively as a tendency to favour certain linguistic options over others (Herdan, 1960), we can then proceed to search for linguistic features which both discriminate well between our genres and can also be computed reliably from unannotated text. Potential sources for such options are comparat ive genre studies (Biber, 1988), authorship attribution research (Holmes, 1998; Forsyth and Holmes, 1996), content analy-