Machine Learning and Natural Language Processing

Dear Colleagues,

Recent years have been marked with the growing availability of natural language processing technologies for practical everyday use. The rapid development of open source instruments, such as NLTK; the wide availability of training corpora; and the general recognition of computational linguistics as an established scientific and technological field has resulted in a wide adoption of language processing in a broad range of software products.

Numerous exciting results were obtained recently with the help of machine learning technologies that make use of available datasets and corpora to support the whole range of tasks addressed in computational linguistics. These approaches were especially beneficial for regional languages, as they receive state-of-the-art language processing tools as soon as the necessary corpora are developed.

However, the existing tools and corpora still cannot cover all of the needs of researchers and developers working in the area of language processing. So, the whole community would benefit from new research perspectives on harnessing the available data, and the creation and adaptation of new linguisitic resources aimed to advance natural language processing technologies.

Thus, we believe that today’s scientific and technological landscape looks positive for research efforts based on a combination of machine learning and natural language processing. Important results can be achieved with the reliance of modern approaches and datasets, and the expected practical impact is higher than ever. This observation motivates us to propose an Issue of Applied Sciences, dedicated specifically to applications of machine learning in natural language processing tasks. We invite both original research and review articles relevant to the proposed topic.

Prof. Maxim Mozgovoy
Dr. Calkin Suero Montero 
Guest Editors

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