An Overview of Empirical Natural Language Processing

In recent years, there has been a resurgence in research on empirical methods in natural language processing. These methods employ learning techniques to automatically extract linguistic knowledge from natural language corpora rather than require the system developer to manually encode the requisite knowledge. This article presents an introduction to the series of specialized articles on these topics and attempts to describe and explain the growing interest in using learning methods to aid the development of natural language processing systems. This special issue presents a machine-learning solution to the linguistic knowledge-acquisition problem: Rather than have a person explicitly provide the computer with information about a language, the computer teaches itself from online text resources. Since its inception, one of the primary goals of AI has been the development of computational methods for natural language understanding. Early research in machine translation illustrated the ...