Neural Networks and Machine Learning for Natural Language Processing - Introduction

The rapid increase of information available on the Internet, much of it textual, calls for computational methods that efficiently organise and classify natural language documents and allow for automatic language acquisition. The last years have seen an increase in conferences, workshops, research degree programs and commercial activities in this area. While the application of neural networks and machine learning techniques to natural language processing is not a recent development, the renewed interest is driven by the need to manage the information explosion of the Internet. A number of new fields, such as Web- and text mining, audio mining and topic detection and tracking\ud (TDT) have emerged and long established areas such as information retrieval and extraction are more relevant than ever.\ud \ud This special issue includes articles which address a number of core questions, including the investigation of the underlying theoretical foundations of machine learning, the implementation and evaluation of methods for learning natural language with neural networks or other machine learning approaches, and applications of such learning systems in various domains