Statistical Semantics: Fundamentals and Applications
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In the field of linguistics, statistical semantics is the application of statistical approaches to the problem of determining the meaning of words or phrases, ideally by unsupervised learning. The goal is to achieve a degree of precision at least sufficient for the purpose of information retrieval.
How You Will Benefit
(I) Insights, and validations about the following topics:
Chapter 1: Statistical semantics
Chapter 2: Computational linguistics
Chapter 3: Natural language processing
Chapter 4: Semantic network
Chapter 5: Word-sense disambiguation
Chapter 6: Latent semantic analysis
Chapter 7: Semantic similarity
Chapter 8: Distributional semantics
Chapter 9: Word embedding
Chapter 10: Semantic parsing
(II) Answering the public top questions about statistical semantics.
(III) Real world examples for the usage of statistical semantics in many fields.
(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of statistical semantics' technologies.
Who This Book Is For
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of statistical semantics.
