Machine Learning , 34, 1-3, Feb. 1999,
Special Issue on Natural Language Learning


Claire Cardie, Cornell University,
Raymond J. Mooney, University of Texas at Austin,

The application of learning techniques to natural language processing has grown dramatically in recent years under the rubric of "corpus-based," "statistical," or "empirical" methods. However, most of this research has been conducted outside the traditional machine learning research community. This special issue is an attempt to bridge this divide by gathering together a variety of recent research papers on various aspects of natural language learning - many from authors who do not generally publish in the traditional machine learning literature - and making them available to the readers of Machine Learning.

Current Status

The special issue appears as Machine Learning 34, 1-3, February 1999. From 31 original submissions, 9 papers were accepted for publication in the special issue. We hope that it becomes an influential issue of the journal and improves the communication and exchange of ideas between machine learning and natural language researchers.

Table of Contents

Call for Papers

Original Call for Papers (deadline long since past)