Эротические рассказы

Natural Language Processing for Social Media. Diana InkpenЧитать онлайн книгу.

Natural Language Processing for Social Media - Diana  Inkpen


Скачать книгу
Tetreault

      2010

      Data-Intensive Text Processing with MapReduce

      Jimmy Lin and Chris Dyer

      2010

      Semantic Role Labeling

      Martha Palmer, Daniel Gildea, and Nianwen Xue

      2010

      Spoken Dialogue Systems

      Kristiina Jokinen and Michael McTear

      2009

      Introduction to Chinese Natural Language Processing

      Kam-Fai Wong, Wenjie Li, Ruifeng Xu, and Zheng-sheng Zhang

      2009

      Introduction to Linguistic Annotation and Text Analytics

      Graham Wilcock

      2009

      Dependency Parsing

      Sandra Kübler, Ryan McDonald, and Joakim Nivre

      2009

      Statistical Language Models for Information Retrieval

      ChengXiang Zhai

      2008

      Copyright © 2020 by Morgan & Claypool

      All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means—electronic, mechanical, photocopy, recording, or any other except for brief quotations in printed reviews, without the prior permission of the publisher.

      Natural Language Processing for Social Media, Third Edition

      Anna Atefeh Farzindar and Diana Inkpen

       www.morganclaypool.com

      ISBN: 9781681738116 paperback

      ISBN: 9781681738123 ebook

      ISBN: 9781681738147 epub

      ISBN: 9781681738130 hardcover

      DOI 10.2200/S00999ED3V01Y202003HLT046

      A Publication in the Morgan & Claypool Publishers series

       SYNTHESIS LECTURES ON HUMAN LANGUAGE TECHNOLOGIES

      Lecture #46

      Series Editor: Grame Hirst, University of Toronto

      Series ISSN

      Print 1947-4040 Electronic 1947-4059

      Cover art illustration by Anna Atefeh Farzindar.

       Natural Language Processing for Social Media

       Third Edition

      Anna Atefeh Farzindar

      University of Southern California

      Diana Inkpen

      University of Ottawa

       SYNTHESIS LECTURES ON HUMAN LANGUAGE TECHNOLOGIES #46

image

       ABSTRACT

      In recent years, online social networking has revolutionized interpersonal communication. The newer research on language analysis in social media has been increasingly focusing on the latter’s impact on our daily lives, both on a personal and a professional level. Natural language processing (NLP) is one of the most promising avenues for social media data processing. It is a scientific challenge to develop powerful methods and algorithms that extract relevant information from a large volume of data coming from multiple sources and languages in various formats or in free form. This book will discuss the challenges in analyzing social media texts in contrast with traditional documents.

      Research methods in information extraction, automatic categorization and clustering, automatic summarization and indexing, and statistical machine translation need to be adapted to a new kind of data. This book reviews the current research on NLP tools and methods for processing the non-traditional information from social media data that is available in large amounts, and it shows how innovative NLP approaches can integrate appropriate linguistic information in various fields such as social media monitoring, health care, and business intelligence. The book further covers the existing evaluation metrics for NLP and social media applications and the new efforts in evaluation campaigns or shared tasks on new datasets collected from social media. Such tasks are organized by the Association for Computational Linguistics (such as SemEval tasks), the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC), or the Conference and Labs of the Evaluation Forum (CLEF).

      In this third edition of the book, the authors added information about recent progress in NLP for social media applications, including more about the modern techniques provided by deep neural networks (DNNs) for modeling language and analyzing social media data.

       KEYWORDS

      social media, social networking, natural language processing, social computing, big data, semantic analysis, artificial intelligence, deep learning

      To my husband Massoud, and my daughters, Tina and Amanda, who are just about the best children a mom could hope for: happy, loving, and fun to be with.

       – Anna Atefeh Farzindar

      To my wonderful husband Nicu with whom I can climb any mountain, and to our sweet daughter Nicoleta.

       – Diana Inkpen

       Contents

       List of Figures

       List of Tables

       Preface

       Acknowledgments

       1 Introduction to Social Media Analysis

       1.1 Introduction

       1.2 Social Media Applications

       1.2.1 Cross-language Document Analysis in Social Media Data

       1.2.2 Deep Learning techniques for Social Media Data

       1.2.3 Real-world Applications

       1.3 Challenges in Social Media Data

       1.4 Semantic Analysis of Social Media

       1.5 Summary

       2 Linguistic Pre-processing of Social Media Texts

      


Скачать книгу
Яндекс.Метрика