Statistical Semantics: Fundamentals and Applications

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.