Relationship Extraction: Fundamentals and Applications

The identification and categorization of semantic relationship mentions within a collection of artifacts, most commonly taken from text or XML documents, is necessary for the completion of a job known as relationship extraction. The process is quite similar to that of information extraction (IE), although IE also needs the elimination of repeated relations (disambiguation) and generally refers to the extraction of a wide variety of various relationships. The goal is extremely similar.

How You Will Benefit

(I) Insights, and validations about the following topics:

Chapter 1: Relationship Extraction

Chapter 2: Semantic Network

Chapter 3: Ontology (computer science)

Chapter 4: Text Mining

Chapter 5: Information Extraction

Chapter 6: Relational Data Mining

Chapter 7: Semantic Similarity

Chapter 8: Ontology Learning

Chapter 9: Knowledge Extraction

Chapter 10: Knowledge Graph

(II) Answering the public top questions about relationship extraction.

(III) Real world examples for the usage of relationship extraction in many fields.

(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of relationship extraction' 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 relationship extraction.