Named Entity Recognition: Fundamentals and Applications

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What Is Named Entity Recognition

Named-entity recognition, or NER, is a subtask of information extraction that seeks to locate and classify named entities mentioned in unstructured text into pre-defined categories such as person names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages, and so on. Other names for this subtask include (named) entity identification, entity chunking, and entity extraction. Named-entity recognition is also known as named-entity identification.


How You Will Benefit


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


Chapter 1: Named-entity recognition


Chapter 2: Natural language processing


Chapter 3: Information extraction


Chapter 4: Named entity


Chapter 5: Relationship extraction


Chapter 6: Outline of natural language processing


Chapter 7: Entity linking


Chapter 8: Apache cTAKES


Chapter 9: SpaCy


Chapter 10: Zero-shot learning


(II) Answering the public top questions about named entity recognition.


(III) Real world examples for the usage of named entity recognition in many fields.


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

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