Following the growing interest in "corpus-based" approaches to computational linguistics, a number of studies have recently appeared on the topic of automatic term recognition or extraction. Because a successful term-recognition method has to be based on proper insights into the nature of terms, studies of automatic term recognition not only contribute to the applications of computational linguistics but also to the theoretical foundation of terminology. Many studies on automatic term recognition treat interesting aspects of terms, but most of them are not well founded and described. This paper tries to give an overview of the principles and methods of automatic term recognition. For that purpose, two major trends are examined, i.e., studies in automatic recognition of significant elements for indexing mainly carried out in information-retrieval circles and current research in automatic term recognition in the field of computational linguistics.

We have developed an automatic composition system for contemporary dance by using 3D motion clips. Our goal is to develop some useful tools in dance education such as creation-support system for teachers and self-study system for students. Our approach is not creating natural connection but creating conceptual sequences using basic motions of contemporary dance. We present an experiment to assess whether sequences randomly selected would be appropriate for contemporary dance training and to determine some effective elements to integrate into the algorithm. As a result of the experiment, our proposed system was found to be useful and helpful for dance training.

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