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What is Word-Sense Disambiguation

Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques
the task/process of selecting the correct sense of a word (usually in context).
Published in Chapter:
Machine Learning in Natural Language Processing
Marina Sokolova (CHEO Research Institute, Canada) and Stan Szpakowicz (University of Ottawa, Canada and Polish Academy of Sciences, Poland)
DOI: 10.4018/978-1-60566-766-9.ch014
Abstract
This chapter presents applications of machine learning techniques to traditional problems in natural language processing, including part-of-speech tagging, entity recognition and word-sense disambiguation. People usually solve such problems without difficulty or at least do a very good job. Linguistics may suggest labour-intensive ways of manually constructing rule-based systems. It is, however, the easy availability of large collections of texts that has made machine learning a method of choice for processing volumes of data well above the human capacity. One of the main purposes of text processing is all manner of information extraction and knowledge extraction from such large text. Machine learning methods discussed in this chapter have stimulated wide-ranging research in natural language processing and helped build applications with serious deployment potential.
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