Musical genre classification is a promising yet difficult task in the field of musical information retrieval. As a widely used feature in genre classification systems, MFCC is typically believed to encode timbral information, since it represents short-duration musical textures. In this paper, we investigate the invariance of MFCC to musical key and tempo, and show that MFCCs in fact encode both...

This article reports on a work-in-progress research on media and information literacy in teamwork and distance work environments. We introduce a theoretical framework that articulates the social and informational dimensions of media and information literacy in the workplace. Based on this framework, we propose a method for investigating the relationship between information literacy and work org...

Introduction. This study reports an investigation into the ways in which people engaged in a serious leisure activity can experience using information to learn (also known as information literacy). Method.Data were collected through twenty-two semistructured, one-on-one, phenomenographic interviews conducted with identified serious leisure participants operating within the area of heritage (as ...

This paper reports on two case studies, the Information and Communications Technology (ICT) adoption among small businesses conducted in both United States and China. One small business from Nebraska (United States of America) and one small business from Sichuan (China) were chosen for comparison. The purpose of this paper is to conduct a comparative case study based on the ICT adoption among s...

In this report we present the work done on the first subtask of the DEFT 2014 challenge which dealt with genre classification of French literary texts. In our approach we developed three types of features : lemmatized words, stylometric features and features that incorporate some form of world knowledge. Subsequent classification experiments were performed using the Balanced Winnow classifier. ...

Developed in the context of Genre Tagging Task at MediaEval 2012, this work consists in automatically assigning genre tags to a set of Internet videos. We approach this task from the classification point of view and focus on different learning strategies: video similarity for processing visual content and an ensemble of classifiers for text-processing. In this paper, we describe the proposed fr...

This paper proposes a novel content-based music genre classification method using temporal information and support vector machine. By processing of texture window statistics and delta computation, temporal information is incorporated to capture the time-varying behavior of music. 7 different temporal evolution descriptors applied in texture window are introduced in this paper, i.e., mean, stand...

In this paper, we propose an audio-visual approach to video genre categorization. It exploits audio, color, temporal and contour information, which are in general genre specific. Audio information is extracted at block-level, which has the advantage of capturing local temporal information. At temporal level, we asses action contents with respect to human perception. Further, color perception is...