This paper introduces Genre and Ontology-based Business Information Architecture Framework (GOBIAF). The aim of Business Information Architecture (BIA) is to support the development of holistic information management principles in geographically dispersed environments. Communication genres and information need interviews are used as a domain analysis method. Ontologies are used as a business in...

Abstract Genre-based approach has been the focus of interest in the teaching of language since the mid1980s. Genre is defined in terms of the use of language in conventionalized communicative settings. The present study made an attempt to scrutinize the effects of genre-based pedagogy on Iranian Pre-intermediate EFL leaners' reading comprehension as well as the interaction between their reading...

Recent theories of focusing and reference rely crucially on discourse structure to constrain the availability of discourse entities for reference, but deriving the structure of an arbitrary discourse has proved to be a significant problem. A useful level of problem reduction may be achieved by analyzing discourse in which the structure is explicit, rather than implicit. In this paper we conside...

We report our findings on using MIDI files and audio features from MIDI, separately and combined together, for MIDI music genre classification. We use McKay and Fujinaga’s 3-root and 9-leaf genre data set. In order to compute distances between MIDI pieces, we use normalized compression distance (NCD). NCD uses the compressed length of a string as an approximation to its Kolmogorov complexity an...

Recently many research has been conducted to retrieve pertinent parameters and adequate models for automatic music genre classification. In this paper, two measures based upon information theory concepts are investigated for mapping the features space to decision space. A Gaussian Mixture Model (GMM) is used as a baseline and reference system. Various strategies are proposed for training and te...

The massive amount of textual data on the Web raises numerous classification problems. Although the notion of domain is widely acknowledged in the IR field, the applicative concept of genre could solve its weaknesses by taking into account the linguistic properties and the document structures of the texts. Two clustering methods are proposed here to illustrate the complementarity of the notions...

This dissertation presents, discusses, and sheds some light on the problems that appear when computers try to automatically classify musical genres from audio signals. In particular, a method is proposed for the automatic music genre classification by using a computational approach that is inspired in music cognition and musicology in addition to Music Information Retrieval techniques. In this ...

Automated Genre Identification (AGI) of web pages is a problem of increasing importance since web genre (e.g. blog, news, eshops, etc.) information can enhance modern Information Retrieval (IR) systems. The state-of-the-art in this field considers AGI as a closed-set classification problem where a variety of web page representation and machine learning models have intensively studied. In this p...

This paper presents an audio genre detection framework that can be used for a multi-language audio corpus. Cepstral coefficients are considered and analyzed as the feature set for both a language dependent and language independent genre identification (GID) task. Language information is found to increase the overall detection accuracy on an average by at least 2.6% from its language independent...

This paper presents the results of two studies that consider the effects of various pedagogical approaches in professional writing classes. The findings indicate that both a moves analysis approach and a chronotopic approach lead to cover letters that have significant lexico-grammatical differences from those written under a nongenre analysis approach. The findings also indicate that cover lett...