ARTIFICIAL INTELLIGENCE AND NATURAL LANGUAGE
PROCESSING
Introduction
Natural Language Processing, or NLP for short, is a subfield of computer science, humanities and
artificial intelligence. Machines can comprehend, interpret, modify and comprehend human
languages due to technological advances. In order to execute tasks like interpretation, autonomous
summarize, Named Entity Recognition (NER), speech recognition, connection recovery and issue
division, it aids developers in organizing knowledge.
Components of NLP
Natural Language Understanding (NLU) by removing the metadata from the material, such
as concepts, entities, keywords, emotions, relations and semantic roles, it aids the machine in
comprehending and analyzing human language.
Natural Language Generation (NLG) acts as a translator, transforming digital data into
representation in natural language. Text planning, Sentence planning and Text Realization are
the three key components.
Application of NLP
Question Answering
Spam Detection
Sentimental Analysis
Machine Translation
Spelling Correction
Speech Recognition
Chatbot
NLP Pipeline
Sentence Segmentation: The first stage in creating the NLP pipeline is sentence
segmentation. It splits the phrase into its text.
Word Tokenization: The statement is divided into individual words or tokens using a word
tokenizer
Stemming: Stemming is a technique used to standardize words into its root or fundamental
form
Lemmatization: Lemmatization and stemming are pretty similar. It is used to group the word's
various inflected forms, known as lemma.
Identifying Stop Words
Dependency Parsing determines the relationship between each word in a phrase
POS tags: Parts of Speech
Name Entity Recognition (NER): The action of finding the stated object, such as an
individual, film, company, or place.
Chunking: Chunking is a technique used to gather little pieces of information and combine
them into longer sentences.
© 2024 Athena Global Education. All Rights Reserved
PROCESSING
Introduction
Natural Language Processing, or NLP for short, is a subfield of computer science, humanities and
artificial intelligence. Machines can comprehend, interpret, modify and comprehend human
languages due to technological advances. In order to execute tasks like interpretation, autonomous
summarize, Named Entity Recognition (NER), speech recognition, connection recovery and issue
division, it aids developers in organizing knowledge.
Components of NLP
Natural Language Understanding (NLU) by removing the metadata from the material, such
as concepts, entities, keywords, emotions, relations and semantic roles, it aids the machine in
comprehending and analyzing human language.
Natural Language Generation (NLG) acts as a translator, transforming digital data into
representation in natural language. Text planning, Sentence planning and Text Realization are
the three key components.
Application of NLP
Question Answering
Spam Detection
Sentimental Analysis
Machine Translation
Spelling Correction
Speech Recognition
Chatbot
NLP Pipeline
Sentence Segmentation: The first stage in creating the NLP pipeline is sentence
segmentation. It splits the phrase into its text.
Word Tokenization: The statement is divided into individual words or tokens using a word
tokenizer
Stemming: Stemming is a technique used to standardize words into its root or fundamental
form
Lemmatization: Lemmatization and stemming are pretty similar. It is used to group the word's
various inflected forms, known as lemma.
Identifying Stop Words
Dependency Parsing determines the relationship between each word in a phrase
POS tags: Parts of Speech
Name Entity Recognition (NER): The action of finding the stated object, such as an
individual, film, company, or place.
Chunking: Chunking is a technique used to gather little pieces of information and combine
them into longer sentences.
© 2024 Athena Global Education. All Rights Reserved
