Download or read book Semantic Role Labeling written by Martha Palmer and published by Springer Nature. This book was released on 2022-05-31 with total page 95 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is aimed at providing an overview of several aspects of semantic role labeling. Chapter 1 begins with linguistic background on the definition of semantic roles and the controversies surrounding them. Chapter 2 describes how the theories have led to structured lexicons such as FrameNet, VerbNet and the PropBank Frame Files that in turn provide the basis for large scale semantic annotation of corpora. This data has facilitated the development of automatic semantic role labeling systems based on supervised machine learning techniques. Chapter 3 presents the general principles of applying both supervised and unsupervised machine learning to this task, with a description of the standard stages and feature choices, as well as giving details of several specific systems. Recent advances include the use of joint inference to take advantage of context sensitivities, and attempts to improve performance by closer integration of the syntactic parsing task with semantic role labeling. Chapter 3 also discusses the impact the granularity of the semantic roles has on system performance. Having outlined the basic approach with respect to English, Chapter 4 goes on to discuss applying the same techniques to other languages, using Chinese as the primary example. Although substantial training data is available for Chinese, this is not the case for many other languages, and techniques for projecting English role labels onto parallel corpora are also presented. Table of Contents: Preface / Semantic Roles / Available Lexical Resources / Machine Learning for Semantic Role Labeling / A Cross-Lingual Perspective / Summary

Download or read book Semantic Role Labeling written by Martha Palmer and published by Morgan & Claypool Publishers. This book was released on 2011-02-02 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is aimed at providing an overview of several aspects of semantic role labeling. Chapter 1 begins with linguistic background on the definition of semantic roles and the controversies surrounding them. Chapter 2 describes how the theories have led to structured lexicons such as FrameNet, VerbNet and the PropBank Frame Files that in turn provide the basis for large scale semantic annotation of corpora. This data has facilitated the development of automatic semantic role labeling systems based on supervised machine learning techniques. Chapter 3 presents the general principles of applying both supervised and unsupervised machine learning to this task, with a description of the standard stages and feature choices, as well as giving details of several specific systems. Recent advances include the use of joint inference to take advantage of context sensitivities, and attempts to improve performance by closer integration of the syntactic parsing task with semantic role labeling. Chapter 3 also discusses the impact the granularity of the semantic roles has on system performance. Having outlined the basic approach with respect to English, Chapter 4 goes on to discuss applying the same techniques to other languages, using Chinese as the primary example. Although substantial training data is available for Chinese, this is not the case for many other languages, and techniques for projecting English role labels onto parallel corpora are also presented. Table of Contents: Preface / Semantic Roles / Available Lexical Resources / Machine Learning for Semantic Role Labeling / A Cross-Lingual Perspective / Summary

Download or read book Hands On Natural Language Processing with Python written by Rajesh Arumugam and published by Packt Publishing Ltd. This book was released on 2018-07-18 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foster your NLP applications with the help of deep learning, NLTK, and TensorFlow Key Features Weave neural networks into linguistic applications across various platforms Perform NLP tasks and train its models using NLTK and TensorFlow Boost your NLP models with strong deep learning architectures such as CNNs and RNNs Book Description Natural language processing (NLP) has found its application in various domains, such as web search, advertisements, and customer services, and with the help of deep learning, we can enhance its performances in these areas. Hands-On Natural Language Processing with Python teaches you how to leverage deep learning models for performing various NLP tasks, along with best practices in dealing with today’s NLP challenges. To begin with, you will understand the core concepts of NLP and deep learning, such as Convolutional Neural Networks (CNNs), recurrent neural networks (RNNs), semantic embedding, Word2vec, and more. You will learn how to perform each and every task of NLP using neural networks, in which you will train and deploy neural networks in your NLP applications. You will get accustomed to using RNNs and CNNs in various application areas, such as text classification and sequence labeling, which are essential in the application of sentiment analysis, customer service chatbots, and anomaly detection. You will be equipped with practical knowledge in order to implement deep learning in your linguistic applications using Python's popular deep learning library, TensorFlow. By the end of this book, you will be well versed in building deep learning-backed NLP applications, along with overcoming NLP challenges with best practices developed by domain experts. What you will learn Implement semantic embedding of words to classify and find entities Convert words to vectors by training in order to perform arithmetic operations Train a deep learning model to detect classification of tweets and news Implement a question-answer model with search and RNN models Train models for various text classification datasets using CNN Implement WaveNet a deep generative model for producing a natural-sounding voice Convert voice-to-text and text-to-voice Train a model to convert speech-to-text using DeepSpeech Who this book is for Hands-on Natural Language Processing with Python is for you if you are a developer, machine learning or an NLP engineer who wants to build a deep learning application that leverages NLP techniques. This comprehensive guide is also useful for deep learning users who want to extend their deep learning skills in building NLP applications. All you need is the basics of machine learning and Python to enjoy the book.

Download or read book The Oxford Handbook of Computational Linguistics written by Ruslan Mitkov and published by Oxford University Press. This book was released on 2004 with total page 808 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook of computational linguistics, written for academics, graduate students and researchers, provides a state-of-the-art reference to one of the most active and productive fields in linguistics.

Download or read book Semantic Features for Semantic Role Labeling written by Liam R. McGrath and published by . This book was released on 2011 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Speech Language Processing written by Dan Jurafsky and published by Pearson Education India. This book was released on 2000-09 with total page 912 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Memory Based Language Processing written by Walter Daelemans and published by Cambridge University Press. This book was released on 2005-09-01 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: Memory-based language processing - a machine learning and problem solving method for language technology - is based on the idea that the direct reuse of examples using analogical reasoning is more suited for solving language processing problems than the application of rules extracted from those examples. This book discusses the theory and practice of memory-based language processing, showing its comparative strengths over alternative methods of language modelling. Language is complex, with few generalizations, many sub-regularities and exceptions, and the advantage of memory-based language processing is that it does not abstract away from this valuable low-frequency information. By applying the model to a range of benchmark problems, the authors show that for linguistic areas ranging from phonology to semantics, it produces excellent results. They also describe TiMBL, a software package for memory-based language processing. The first comprehensive overview of the approach, this book will be invaluable for computational linguists, psycholinguists and language engineers.

Download or read book Semantic Role Labeling Using Rich Morphological Features written by and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Robust Semantic Role Labeling written by Yi Szu-Ting and published by LAP Lambert Academic Publishing. This book was released on 2015-05-25 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: Correctly identifying semantic entities and successfully disambiguating the relations between them and their predicates is an important and necessary step for successful natural language processing applications, such as text summarization, question answering, and machine translation. Researchers have studied this problem, semantic role labeling (SRL), as a machine learning problem since 2000. However, after using an optimal global inference algorithm to combine several SRL systems, the growth of SRL performance seems to have reached a plateau. Syntactic parsing is the bottleneck of the task of semantic role labeling and robustness is the ultimate goal. In this book, we investigate ways to train a better syntactic parser and increase SRL system robustness. We demonstrate that parse trees augmented by semantic role markups can serve as suitable training data for training a parser for an SRL system. For system robustness, we propose that it is easier to learn a new set of semantic roles. The new roles are less verb- dependent than the original PropBank roles. As a result, the SRL system trained on the new roles achieves significantly better robustness.

Download or read book The Art and Science of Analyzing Software Data written by Christian Bird and published by Elsevier. This book was released on 2015-09-02 with total page 673 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Art and Science of Analyzing Software Data provides valuable information on analysis techniques often used to derive insight from software data. This book shares best practices in the field generated by leading data scientists, collected from their experience training software engineering students and practitioners to master data science. The book covers topics such as the analysis of security data, code reviews, app stores, log files, and user telemetry, among others. It covers a wide variety of techniques such as co-change analysis, text analysis, topic analysis, and concept analysis, as well as advanced topics such as release planning and generation of source code comments. It includes stories from the trenches from expert data scientists illustrating how to apply data analysis in industry and open source, present results to stakeholders, and drive decisions. Presents best practices, hints, and tips to analyze data and apply tools in data science projects Presents research methods and case studies that have emerged over the past few years to further understanding of software data Shares stories from the trenches of successful data science initiatives in industry

Download or read book Natural Language Annotation for Machine Learning written by James Pustejovsky and published by "O'Reilly Media, Inc.". This book was released on 2013 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Includes bibliographical references (p. 305-315) and index.

Download or read book The Structure of Modern English written by Laurel J. Brinton and published by John Benjamins Publishing. This book was released on 2000-01-01 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text is designed for undergraduate and graduate students interested in contemporary English, especially those whose primary area of interest is English as a second language. Focus is placed exclusively on English data, providing an empirical explication of the structure of the language.

Download or read book Ten Lectures on Event Structure in a Network Theory of Language written by Nikolas Gisborne and published by BRILL. This book was released on 2020-08-31 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Ten Lectures on Event Structure in a Network Theory of Language, Nikolas Gisborne offers an account of verb meaning from the perspective of a model that treats language structure as part of the wider cognitive network.

Download or read book English Verb Classes and Alternations written by Beth Levin and published by University of Chicago Press. This book was released on 1993-09 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this rich reference work, Beth Levin classifies over 3,000 English verbs according to shared meaning and behavior. Levin starts with the hypothesis that a verb's meaning influences its syntactic behavior and develops it into a powerful tool for studying the English verb lexicon. She shows how identifying verbs with similar syntactic behavior provides an effective means of distinguishing semantically coherent verb classes, and isolates these classes by examining verb behavior with respect to a wide range of syntactic alternations that reflect verb meaning. The first part of the book sets out alternate ways in which verbs can express their arguments. The second presents classes of verbs that share a kernel of meaning and explores in detail the behavior of each class, drawing on the alternations in the first part. Levin's discussion of each class and alternation includes lists of relevant verbs, illustrative examples, comments on noteworthy properties, and bibliographic references. The result is an original, systematic picture of the organization of the verb inventory. Easy to use, English Verb Classes and Alternations sets the stage for further explorations of the interface between lexical semantics and syntax. It will prove indispensable for theoretical and computational linguists, psycholinguists, cognitive scientists, lexicographers, and teachers of English as a second language.

Download or read book Advanced Technologies Systems and Applications VI written by Naida Ademović and published by Springer Nature. This book was released on 2021-11-16 with total page 803 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the innovative and interdisciplinary application of advanced technologies. It includes the scientific outcomes and results of the conference 12th Day of Bosnian-Herzegovinian American Academy of Art and Sciences held in Mostar, Bosnia, and Herzegovina, June 24-27, 2021. The latest developments in various fields of engineering have been presented through various papers in civil engineering, mechanical engineering, computing, electrical and electronics engineering, and others. A new session, Sustainable Urban Development: Designing Smart, Inclusive and Resilient Cities, was organized, enabling experts in this field to exchange their knowledge and expertise.

Download or read book Sentic Computing written by Erik Cambria and published by Springer Science & Business Media. This book was released on 2012-07-28 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book common sense computing techniques are further developed and applied to bridge the semantic gap between word-level natural language data and the concept-level opinions conveyed by these. In particular, the ensemble application of graph mining and multi-dimensionality reduction techniques is exploited on two common sense knowledge bases to develop a novel intelligent engine for open-domain opinion mining and sentiment analysis. The proposed approach, termed sentic computing, performs a clause-level semantic analysis of text, which allows the inference of both the conceptual and emotional information associated with natural language opinions and, hence, a more efficient passage from (unstructured) textual information to (structured) machine-processable data.

Download or read book Chinese Lexical Semantics written by Jia-Fei Hong and published by Springer Nature. This book was released on 2020-01-03 with total page 873 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-workshop proceedings of the 20th Chinese Lexical Semantics Workshop, CLSW 2019, held in Chiayi, Taiwan, in June 2019. The 39 full papers and 46 short papers included in this volume were carefully reviewed and selected from 254 submissions. They are organized in the following topical sections: lexical semantics; applications of natural language processing; lexical resources; corpus linguistics.