July 2017
Beginner to intermediate
486 pages
13h 49m
English
Word-sense disambiguation (WSD) is a well-known problem in NLP. First of all, let's understand what WSD is. WSD is used in identifying what the sense of a word means in a sentence when the word has multiple meanings. When a single word has multiple meaning, then for the machine it is difficult to identify the correct meaning and to solve this challenging issue we can use the rule-based system or machine learning techniques.
In this chapter, our focus area is the RB system. So, we will see the flow of how WSD is solved. In order to solve this complex problem using the RB system, you can take the following steps:
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