Natural language and machine translation

The World Wide Web constitutes the largest existing source of texts written in a great variety of languages.

This book introduces Chinese language-processing issues and techniques to readers who already have a basic background in natural language processing (NLP).

In the last few years, a number of NLP researchers have developed and participated in the task of Recognizing Textual Entailment (RTE).

In the last few years, a number of NLP researchers have developed and participated in the task of Recognizing Textual Entailment (RTE).

This book is aimed at providing an overview of several aspects of semantic role labeling.

Search for information is no longer exclusively limited within the native language of the user, but is more and more extended to other languages.

Dependency-based methods for syntactic parsing have become increasingly popular in natural language processing in recent years.

With rapid urbanization defining the 21st Century, cities face mounting challenges in achieving sustainability, equity, and functionality.

Take a new approach to digital marketing based on transparency, relevance, and delivering real value to your audience.

The computational approach of this book is aimed at simulating the human ability to understand various kinds of phrases with a novel metaphoric component.

The computational approach of this book is aimed at simulating the human ability to understand various kinds of phrases with a novel metaphoric component.

"e;Ultra Low Bit-Rate Speech Coding"e; focuses on the specialized topic of speech coding at very low bit-rates of 1 Kbits/sec and less, particularly at the lower ends of this range, down to 100 bps.

What value does semantic data modeling offer?

What value does semantic data modeling offer?

Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets.

Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets.

Companies are spending billions on machine learning projects, but its money wasted if the models cant be deployed effectively.

Companies are spending billions on machine learning projects, but its money wasted if the models cant be deployed effectively.

Many industry experts consider unsupervised learning the next frontier in artificial intelligence, one that may hold the key to general artificial intelligence.

Many industry experts consider unsupervised learning the next frontier in artificial intelligence, one that may hold the key to general artificial intelligence.

Learn how to fuse today's data science tools and techniques with your SAP enterprise resource planning (ERP) system.

Learn how to fuse today's data science tools and techniques with your SAP enterprise resource planning (ERP) system.

With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning.

With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning.

If you want to build an enterprise-quality application that uses natural language text but arent sure where to begin or what tools to use, this practical guide will help get you started.

If you want to build an enterprise-quality application that uses natural language text but arent sure where to begin or what tools to use, this practical guide will help get you started.

Natural Language Processing (NLP) provides boundless opportunities for solving problems in artificial intelligence, making products such as Amazon Alexa and Google Translate possible.

Natural Language Processing (NLP) provides boundless opportunities for solving problems in artificial intelligence, making products such as Amazon Alexa and Google Translate possible.

Learn how to solve challenging machine learning problems with TensorFlow, Googles revolutionary new software library for deep learning.

Learn how to solve challenging machine learning problems with TensorFlow, Googles revolutionary new software library for deep learning.

Much of the data available today is unstructured and text-heavy, making it challenging for analysts to apply their usual data wrangling and visualization tools.

Much of the data available today is unstructured and text-heavy, making it challenging for analysts to apply their usual data wrangling and visualization tools.

From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data.

Master NLP with R using practical techniques and tools, featuring in-depth coverage of modern NLP models and libraries.

Get hints, useful tricks, and solutions to those annoying problems that plague users of Microsoft's ever-popular word processing software.

In this book, Harley Hahn demystifies Emacs for programmers, students, and everyday users.

The content and screenshots in this book are based on SharePoint 2013.

The present volume contains some selected topics of current interest around the world in the mathematical analysis of natural language.

Parallel and Distributed Information Systems brings together in one place important contributions and up-to-date research results in this fast moving area.

One of the aims of Natural Language Processing is to facilitate .

Internet and web technology penetrates many aspects of our daily life.

Concurrency in Dependable Computing focuses on concurrency related issues in the area of dependable computing.

A central problem of natural language generation is that of 'expressibility'.

The key assumption in this text is that machine translation is not merely a mechanical process but in fact requires a high level of linguistic sophistication, as the nuances of syntax, semantics and intonation cannot always be conveyed by modern technology.