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Information in today's advancing world is rapidly expanding and
becoming widely available. This eruption of data has made handling
it a daunting and time-consuming task. Natural language processing
(NLP) is a method that applies linguistics and algorithms to large
amounts of this data to make it more valuable. NLP improves the
interaction between humans and computers, yet there remains a lack
of research that focuses on the practical implementations of this
trending approach. Neural Networks for Natural Language Processing
is a collection of innovative research on the methods and
applications of linguistic information processing and its
computational properties. This publication will support readers
with performing sentence classification and language generation
using neural networks, apply deep learning models to solve machine
translation and conversation problems, and apply deep structured
semantic models on information retrieval and natural language
applications. While highlighting topics including deep learning,
query entity recognition, and information retrieval, this book is
ideally designed for research and development professionals, IT
specialists, industrialists, technology developers, data analysts,
data scientists, academics, researchers, and students seeking
current research on the fundamental concepts and techniques of
natural language processing.
Information in today's advancing world is rapidly expanding and
becoming widely available. This eruption of data has made handling
it a daunting and time-consuming task. Natural language processing
(NLP) is a method that applies linguistics and algorithms to large
amounts of this data to make it more valuable. NLP improves the
interaction between humans and computers, yet there remains a lack
of research that focuses on the practical implementations of this
trending approach. Neural Networks for Natural Language Processing
is a collection of innovative research on the methods and
applications of linguistic information processing and its
computational properties. This publication will support readers
with performing sentence classification and language generation
using neural networks, apply deep learning models to solve machine
translation and conversation problems, and apply deep structured
semantic models on information retrieval and natural language
applications. While highlighting topics including deep learning,
query entity recognition, and information retrieval, this book is
ideally designed for research and development professionals, IT
specialists, industrialists, technology developers, data analysts,
data scientists, academics, researchers, and students seeking
current research on the fundamental concepts and techniques of
natural language processing.
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