Framework and Resources for Natural Language Parser Evaluation

Framework and Resources for Natural Language Parser Evaluation PDF Author: Tuomo Kakkonen
Publisher: Tuomo Kakkonen
ISBN: 9522190594
Category :
Languages : en
Pages : 264

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Framework and Resources for Natural Language Parser Evaluation

Framework and Resources for Natural Language Parser Evaluation PDF Author: Tuomo Kakkonen
Publisher: Tuomo Kakkonen
ISBN: 9522190594
Category :
Languages : en
Pages : 264

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Book Description


Framework and Resources for Natural Language Parser Evaluation

Framework and Resources for Natural Language Parser Evaluation PDF Author: Tuomo Kakkonen
Publisher: Tuomo Kakkonen
ISBN: 9789522190581
Category :
Languages : en
Pages : 250

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Natural Language Processing with Python

Natural Language Processing with Python PDF Author: Steven Bird
Publisher: "O'Reilly Media, Inc."
ISBN: 0596555717
Category : Computers
Languages : en
Pages : 506

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Book Description
This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.

Advances in Natural Language Processing

Advances in Natural Language Processing PDF Author: Tapio Salakoski
Publisher: Springer Science & Business Media
ISBN: 3540373349
Category : Computers
Languages : en
Pages : 784

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Book Description
This book constitutes the refereed proceedings of the 5th International Conference on Natural Language Processing, FinTAL 2006, held in Turku, Finland in August 2006. The book presents 72 revised full papers together with 1 invited talk and the extended abstracts of 2 invited keynote addresses. The papers address all current issues in computational linguistics and monolingual and multilingual intelligent language processing - theory, methods and applications.

Evaluating Natural Language Processing Systems

Evaluating Natural Language Processing Systems PDF Author: Karen Sparck Jones
Publisher: Springer Science & Business Media
ISBN: 9783540613091
Category : Computers
Languages : en
Pages : 256

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Book Description
This book is about the patterns of connections between brain structures. It reviews progress on the analysis of neuroanatomical connection data and presents six different approaches to data analysis. The results of their application to data from cat and monkey cortex are explored. This volume sheds light on the organization of the brain that is specified by its wiring.

Statistical Significance Testing for Natural Language Processing

Statistical Significance Testing for Natural Language Processing PDF Author: Rotem Dror
Publisher: Morgan & Claypool Publishers
ISBN: 1681737965
Category : Computers
Languages : en
Pages : 118

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Book Description
Data-driven experimental analysis has become the main evaluation tool of Natural Language Processing (NLP) algorithms. In fact, in the last decade, it has become rare to see an NLP paper, particularly one that proposes a new algorithm, that does not include extensive experimental analysis, and the number of involved tasks, datasets, domains, and languages is constantly growing. This emphasis on empirical results highlights the role of statistical significance testing in NLP research: If we, as a community, rely on empirical evaluation to validate our hypotheses and reveal the correct language processing mechanisms, we better be sure that our results are not coincidental. The goal of this book is to discuss the main aspects of statistical significance testing in NLP. Our guiding assumption throughout the book is that the basic question NLP researchers and engineers deal with is whether or not one algorithm can be considered better than another one. This question drives the field forward as it allows the constant progress of developing better technology for language processing challenges. In practice, researchers and engineers would like to draw the right conclusion from a limited set of experiments, and this conclusion should hold for other experiments with datasets they do not have at their disposal or that they cannot perform due to limited time and resources. The book hence discusses the opportunities and challenges in using statistical significance testing in NLP, from the point of view of experimental comparison between two algorithms. We cover topics such as choosing an appropriate significance test for the major NLP tasks, dealing with the unique aspects of significance testing for non-convex deep neural networks, accounting for a large number of comparisons between two NLP algorithms in a statistically valid manner (multiple hypothesis testing), and, finally, the unique challenges yielded by the nature of the data and practices of the field.

Advances in Natural Language Processing

Advances in Natural Language Processing PDF Author: Hrafn Loftsson
Publisher: Springer
ISBN: 3642147704
Category : Computers
Languages : en
Pages : 443

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Book Description
This book constitutes the proceedings of the 7th International Conference on Advances in Natural Language Processing held in Reykjavik, Iceland, in August 2010.

Collaborative Annotation for Reliable Natural Language Processing

Collaborative Annotation for Reliable Natural Language Processing PDF Author: Karën Fort
Publisher: John Wiley & Sons
ISBN: 1119307651
Category : Computers
Languages : en
Pages : 122

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Book Description
This book presents a unique opportunity for constructing a consistent image of collaborative manual annotation for Natural Language Processing (NLP). NLP has witnessed two major evolutions in the past 25 years: firstly, the extraordinary success of machine learning, which is now, for better or for worse, overwhelmingly dominant in the field, and secondly, the multiplication of evaluation campaigns or shared tasks. Both involve manually annotated corpora, for the training and evaluation of the systems. These corpora have progressively become the hidden pillars of our domain, providing food for our hungry machine learning algorithms and reference for evaluation. Annotation is now the place where linguistics hides in NLP. However, manual annotation has largely been ignored for some time, and it has taken a while even for annotation guidelines to be recognized as essential. Although some efforts have been made lately to address some of the issues presented by manual annotation, there has still been little research done on the subject. This book aims to provide some useful insights into the subject. Manual corpus annotation is now at the heart of NLP, and is still largely unexplored. There is a need for manual annotation engineering (in the sense of a precisely formalized process), and this book aims to provide a first step towards a holistic methodology, with a global view on annotation.

Handbook of Linguistic Annotation

Handbook of Linguistic Annotation PDF Author: Nancy Ide
Publisher: Springer
ISBN: 9402408819
Category : Language Arts & Disciplines
Languages : en
Pages : 1440

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Book Description
This handbook offers a thorough treatment of the science of linguistic annotation. Leaders in the field guide the reader through the process of modeling, creating an annotation language, building a corpus and evaluating it for correctness. Essential reading for both computer scientists and linguistic researchers.Linguistic annotation is an increasingly important activity in the field of computational linguistics because of its critical role in the development of language models for natural language processing applications. Part one of this book covers all phases of the linguistic annotation process, from annotation scheme design and choice of representation format through both the manual and automatic annotation process, evaluation, and iterative improvement of annotation accuracy. The second part of the book includes case studies of annotation projects across the spectrum of linguistic annotation types, including morpho-syntactic tagging, syntactic analyses, a range of semantic analyses (semantic roles, named entities, sentiment and opinion), time and event and spatial analyses, and discourse level analyses including discourse structure, co-reference, etc. Each case study addresses the various phases and processes discussed in the chapters of part one.

Mining Scientific Papers: NLP-enhanced Bibliometrics

Mining Scientific Papers: NLP-enhanced Bibliometrics PDF Author: Iana Atanassova
Publisher: Frontiers Media SA
ISBN: 2889459640
Category :
Languages : en
Pages : 134

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Book Description