Abstract

The purpose of this book is to present a collection of papers that represents a broad spectrum of current research in learning methods for natural language processing, and to advance the state of the art in language learning and artificial intelligence. The book should bridge a gap between several areas that are usually discussed separately, including connectionist, statistical, and symbolic methods. In order to bring together new and different language learning approaches, we held a workshop at the International Joint Conference on Artificial Intelligence in Montreal in August 1995. Paper contributions were selected and revised after having been reviewed by at least twomembers of the international program committee as well as additional reviewers. This book contains the revised workshop papers and additional papers by members of the program committee. In particular this book focuses on current issues such as: -- How can we apply existing learning methods to language processing? -- What new learning methods are needed for language processing and why? -- What language knowledge should be learned and why?

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