Graph Learning And Network Science For Natural Language Processing

DOWNLOAD

Download Graph Learning And Network Science For Natural Language Processing PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Graph Learning And Network Science For Natural Language Processing book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page

Graph Learning And Network Science For Natural Language Processing

DOWNLOAD
Author : Muskan Garg
language : en
Publisher: CRC Press
Release Date : 2022-12-28

Graph Learning And Network Science For Natural Language Processing written by Muskan Garg and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-28 with Business & Economics categories.

Advances in graph-based natural language processing (NLP) and information retrieval tasks have shown the importance of processing using the Graph of Words method. This book covers recent concrete information, from the basics to advanced level, about graph-based learning, such as neural network-based approaches, computational intelligence for learning parameters and feature reduction, and network science for graph-based NPL. It also contains information about language generation based on graphical theories and language models. Features: Presents a comprehensive study of the interdisciplinary graphical approach to NLP Covers recent computational intelligence techniques for graph-based neural network models Discusses advances in random walk-based techniques, semantic webs, and lexical networks Explores recent research into NLP for graph-based streaming data Reviews advances in knowledge graph embedding and ontologies for NLP approaches This book is aimed at researchers and graduate students in computer science, natural language processing, and deep and machine learning.

Graph Learning And Network Science For Natural Language Processing

DOWNLOAD
Author : Muskan Garg
language : en
Publisher: CRC Press
Release Date : 2022-12-28

Graph Learning And Network Science For Natural Language Processing written by Muskan Garg and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-28 with Business & Economics categories.

Advances in graph-based natural language processing (NLP) and information retrieval tasks have shown the importance of processing using the Graph of Words method. This book covers recent concrete information, from the basics to advanced level, about graph-based learning, such as neural network-based approaches, computational intelligence for learning parameters and feature reduction, and network science for graph-based NPL. It also contains information about language generation based on graphical theories and language models. Features: Presents a comprehensive study of the interdisciplinary graphical approach to NLP Covers recent computational intelligence techniques for graph-based neural network models Discusses advances in random walk-based techniques, semantic webs, and lexical networks Explores recent research into NLP for graph-based streaming data Reviews advances in knowledge graph embedding and ontologies for NLP approaches This book is aimed at researchers and graduate students in computer science, natural language processing, and deep and machine learning.

Network Science With Python

DOWNLOAD
Author : David Knickerbocker
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-02-28

Network Science With Python written by David Knickerbocker and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-28 with Computers categories.

Discover the use of graph networks to develop a new approach to data science using theoretical and practical methods with this expert guide using Python, printed in color Key FeaturesCreate networks using data points and informationLearn to visualize and analyze networks to better understand communitiesExplore the use of network data in both - supervised and unsupervised machine learning projectsPurchase of the print or Kindle book includes a free PDF eBookBook Description Network analysis is often taught with tiny or toy data sets, leaving you with a limited scope of learning and practical usage. Network Science with Python helps you extract relevant data, draw conclusions and build networks using industry-standard – practical data sets. You'll begin by learning the basics of natural language processing, network science, and social network analysis, then move on to programmatically building and analyzing networks. You'll get a hands-on understanding of the data source, data extraction, interaction with it, and drawing insights from it. This is a hands-on book with theory grounding, specific technical, and mathematical details for future reference. As you progress, you'll learn to construct and clean networks, conduct network analysis, egocentric network analysis, community detection, and use network data with machine learning. You'll also explore network analysis concepts, from basics to an advanced level. By the end of the book, you'll be able to identify network data and use it to extract unconventional insights to comprehend the complex world around you. What you will learnExplore NLP, network science, and social network analysisApply the tech stack used for NLP, network science, and analysisExtract insights from NLP and network dataGenerate personalized NLP and network projectsAuthenticate and scrape tweets, connections, the web, and data streamsDiscover the use of network data in machine learning projectsWho this book is for Network Science with Python demonstrates how programming and social science can be combined to find new insights. Data scientists, NLP engineers, software engineers, social scientists, and data science students will find this book useful. An intermediate level of Python programming is a prerequisite. Readers from both – social science and programming backgrounds will find a new perspective and add a feather to their hat.

Neural Networks For Natural Language Processing

DOWNLOAD
Author : S., Sumathi
language : en
Publisher: IGI Global
Release Date : 2019-11-29

Neural Networks For Natural Language Processing written by S., Sumathi and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-29 with Computers categories.

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.

Graph Neural Networks For Natural Language Processing

DOWNLOAD
Author : LINGFEI WU; YU CHEN; KAI SHEN; XIAOJIE GUO; HANNIN.
language : en
Publisher:
Release Date : 2023

Graph Neural Networks For Natural Language Processing written by LINGFEI WU; YU CHEN; KAI SHEN; XIAOJIE GUO; HANNIN. and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with COMPUTERS categories.

Deep learning has become the dominant approach in addressing various tasks in Natural Language Processing (NLP). Although text inputs are typically represented as a sequence of tokens, there is a rich variety of NLP problems that can be best expressed with a graph structure. As a result, there is a surge of interest in developing new deep learning techniques on graphs for a large number of NLP tasks. In this monograph, the authors present a comprehensive overview on Graph Neural Networks (GNNs) for Natural Language Processing. They propose a new taxonomy of GNNs for NLP, which systematically organizes existing research of GNNs for NLP along three axes: graph construction, graph representation learning, and graph based encoder-decoder models. They further introduce a large number of NLP applications that exploits the power of GNNs and summarize the corresponding benchmark datasets, evaluation metrics, and open-source codes. Finally, they discuss various outstanding challenges for making the full use of GNNs for NLP as well as future research directions. This is the first comprehensive overview of Graph Neural Networks for Natural Language Processing. It provides students and researchers with a concise and accessible resource to quickly get up to speed with an important area of machine learning research.

Mathematical Reviews

DOWNLOAD
Author :
language : en
Publisher:
Release Date : 2005

Mathematical Reviews written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Mathematics categories.

Representation Learning For Natural Language Processing

DOWNLOAD
Author : Zhiyuan Liu
language : en
Publisher: Springer Nature
Release Date : 2023-08-23

Representation Learning For Natural Language Processing written by Zhiyuan Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-23 with Computers categories.

This book provides an overview of the recent advances in representation learning theory, algorithms, and applications for natural language processing (NLP), ranging from word embeddings to pre-trained language models. It is divided into four parts. Part I presents the representation learning techniques for multiple language entries, including words, sentences and documents, as well as pre-training techniques. Part II then introduces the related representation techniques to NLP, including graphs, cross-modal entries, and robustness. Part III then introduces the representation techniques for the knowledge that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, legal domain knowledge and biomedical domain knowledge. Lastly, Part IV discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing. As compared to the first edition, the second edition (1) provides a more detailed introduction to representation learning in Chapter 1; (2) adds four new chapters to introduce pre-trained language models, robust representation learning, legal knowledge representation learning and biomedical knowledge representation learning; (3) updates recent advances in representation learning in all chapters; and (4) corrects some errors in the first edition. The new contents will be approximately 50%+ compared to the first edition. This is an open access book.

Deep Learning On Graphs

DOWNLOAD
Author : Yao Ma
language : en
Publisher: Cambridge University Press
Release Date : 2021-09-23

Deep Learning On Graphs written by Yao Ma and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-23 with Computers categories.

A comprehensive text on foundations and techniques of graph neural networks with applications in NLP, data mining, vision and healthcare.

Directory Of Postgraduate Studies 2002

DOWNLOAD
Author : Hobsons Publishing, PLC
language : en
Publisher:
Release Date : 2001

Directory Of Postgraduate Studies 2002 written by Hobsons Publishing, PLC and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Universities and colleges categories.

Peterson S Guide To Graduate Programs In Engineering And Applied Sciences

DOWNLOAD
Author :
language : en
Publisher:
Release Date : 1991

Peterson S Guide To Graduate Programs In Engineering And Applied Sciences written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with Engineering categories.