Semantic Analysis

This chapter studies semantic analysis, one of the core concepts for learning NLP. There are two basic schemes of semantic analysis: lexical and compositional semantic analysis. After that we will explore word senses and six commonly used lexical semantics followed by word sense disambiguation (WSD) and various WSD schemes. Further, it also studies WordNet and online thesauri for word similarity and various distributed similarity measurement include Point-wise Mutual Information (PMI) and Positive Point-wise Mutual information (PPMI) models with live examples for illustration. Chapters 4 and 5 also serve as the conceptual basis for Workshop#4—Semantic Analysis and Word Vectors using spaCy in Chap. 13 .