Statistical Semantics: Fundamentals and Applications

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What Is Statistical Semantics

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.

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