Inductive Dependency Parsing PDF Download

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Inductive Dependency Parsing

Inductive Dependency Parsing PDF Author: Joakim Nivre
Publisher: Springer Science & Business Media
ISBN: 1402048890
Category : Computers
Languages : en
Pages : 224

Book Description
This book describes the framework of inductive dependency parsing, a methodology for robust and efficient syntactic analysis of unrestricted natural language text. Coverage includes a theoretical analysis of central models and algorithms, and an empirical evaluation of memory-based dependency parsing using data from Swedish and English. A one-stop reference to dependency-based parsing of natural language, it will interest researchers and system developers in language technology, and is suitable for graduate or advanced undergraduate courses.

Inductive Dependency Parsing

Inductive Dependency Parsing PDF Author: Joakim Nivre
Publisher: Springer Science & Business Media
ISBN: 1402048890
Category : Computers
Languages : en
Pages : 224

Book Description
This book describes the framework of inductive dependency parsing, a methodology for robust and efficient syntactic analysis of unrestricted natural language text. Coverage includes a theoretical analysis of central models and algorithms, and an empirical evaluation of memory-based dependency parsing using data from Swedish and English. A one-stop reference to dependency-based parsing of natural language, it will interest researchers and system developers in language technology, and is suitable for graduate or advanced undergraduate courses.

Inductive Dependency Parsing

Inductive Dependency Parsing PDF Author: Joakim Nivre
Publisher: Springer
ISBN: 9781402048883
Category : Computers
Languages : en
Pages : 212

Book Description
This book describes the framework of inductive dependency parsing, a methodology for robust and efficient syntactic analysis of unrestricted natural language text. Coverage includes a theoretical analysis of central models and algorithms, and an empirical evaluation of memory-based dependency parsing using data from Swedish and English. A one-stop reference to dependency-based parsing of natural language, it will interest researchers and system developers in language technology, and is suitable for graduate or advanced undergraduate courses.

Inductive Dependency Parsing of Natural Language Text

Inductive Dependency Parsing of Natural Language Text PDF Author: Joakim Nivre
Publisher:
ISBN:
Category :
Languages : en
Pages : 209

Book Description


Dependency Parsing

Dependency Parsing PDF Author: Sandra Kübler
Publisher: Morgan & Claypool Publishers
ISBN: 1598295969
Category : Computers
Languages : en
Pages : 128

Book Description
Dependency-based methods for syntactic parsing have become increasingly popular in natural language processing in recent years. This book gives a thorough introduction to the methods that are most widely used today. After an introduction to dependency grammar and dependency parsing, followed by a formal characterization of the dependency parsing problem, the book surveys the three major classes of parsing models that are in current use: transition-based, graph-based, and grammar-based models. It continues with a chapter on evaluation and one on the comparison of different methods, and it closes with a few words on current trends and future prospects of dependency parsing. The book presupposes a knowledge of basic concepts in linguistics and computer science, as well as some knowledge of parsing methods for constituency-based representations. Table of Contents: Introduction / Dependency Parsing / Transition-Based Parsing / Graph-Based Parsing / Grammar-Based Parsing / Evaluation / Comparison / Final Thoughts

Improving Dependency Parsing Using Word Clusters

Improving Dependency Parsing Using Word Clusters PDF Author: Jostein Lien
Publisher: LAP Lambert Academic Publishing
ISBN: 9783659794551
Category :
Languages : en
Pages : 120

Book Description
Several studies have attempted to improve the accuracy in dependency parsing by including information about word clusters into the parsing models. The use of word clusters are typically motivated by the shortage of labeled training data and domain adaption, attempting to influence a parsing model for use on data from a new domain. This book shows the effect of using cluster-based features in MaltParser, a data-driven parser for inductive dependency parsing. Different clustering features are used for generating clusters, using the K-means clustering algorithm. The clusters are used as a source of additional information in an expanded feature model used by the MaltParser system. Parsing experiments are performed on several different data sets, including the Wall Street Journal and texts from various web domains. Significantly improved parsing results are reported when using a cluster-informed parser compared to the baseline parser. The contents of this book might be of interest to anyone interested in the application of machine learning in language technology.

Dependency Parsing

Dependency Parsing PDF Author: Sandra Kubler
Publisher: Springer Nature
ISBN: 3031021312
Category : Computers
Languages : en
Pages : 115

Book Description
Dependency-based methods for syntactic parsing have become increasingly popular in natural language processing in recent years. This book gives a thorough introduction to the methods that are most widely used today. After an introduction to dependency grammar and dependency parsing, followed by a formal characterization of the dependency parsing problem, the book surveys the three major classes of parsing models that are in current use: transition-based, graph-based, and grammar-based models. It continues with a chapter on evaluation and one on the comparison of different methods, and it closes with a few words on current trends and future prospects of dependency parsing. The book presupposes a knowledge of basic concepts in linguistics and computer science, as well as some knowledge of parsing methods for constituency-based representations. Table of Contents: Introduction / Dependency Parsing / Transition-Based Parsing / Graph-Based Parsing / Grammar-Based Parsing / Evaluation / Comparison / Final Thoughts

Semi-Supervised Dependency Parsing

Semi-Supervised Dependency Parsing PDF Author: Wenliang Chen
Publisher: Springer
ISBN: 9812875522
Category : Language Arts & Disciplines
Languages : en
Pages : 149

Book Description
This book presents a comprehensive overview of semi-supervised approaches to dependency parsing. Having become increasingly popular in recent years, one of the main reasons for their success is that they can make use of large unlabeled data together with relatively small labeled data and have shown their advantages in the context of dependency parsing for many languages. Various semi-supervised dependency parsing approaches have been proposed in recent works which utilize different types of information gleaned from unlabeled data. The book offers readers a comprehensive introduction to these approaches, making it ideally suited as a textbook for advanced undergraduate and graduate students and researchers in the fields of syntactic parsing and natural language processing.

Semantics in Adaptive and Personalised Systems

Semantics in Adaptive and Personalised Systems PDF Author: Pasquale Lops
Publisher: Springer Nature
ISBN: 303005618X
Category : Computers
Languages : en
Pages : 186

Book Description
This monograph gives a complete overview of the techniques and the methods for semantics-aware content representation and shows how to apply such techniques in various use cases, such as recommender systems, user profiling and social media analysis. Throughout the book, the authors provide an extensive analysis of the techniques currently proposed in the literature and cover all the available tools and libraries to implement and exploit such methodologies in real-world scenarios. The book first introduces the problem of information overload and the reasons why content-based information needs to be taken into account. Next, the basics of Natural Language Processing are provided, by describing operations such as tokenization, stopword removal, lemmatization, stemming, part-of-speech tagging, along with the main problems and issues. Finally, the book describes the different approaches for semantics-aware content representation: such approaches are split into ‘exogenous’ and ‘endogenous’ ones, depending on whether external knowledge sources as DBpedia or geometrical models and distributional semantics are used, respectively. To conclude, several successful use cases and an extensive list of available tools and resources to implement the approaches are shown. Semantics in Adaptive and Personalised Systems definitely fills the gap between the extensive literature on content-based recommender systems, natural language processing, and the different types of semantics-aware representations.

Advances in Natural Language Processing

Advances in Natural Language Processing PDF Author: Bengt Nordström
Publisher: Springer Science & Business Media
ISBN: 3540852867
Category : Computers
Languages : en
Pages : 522

Book Description
This book constitutes the refereed proceedings of the 6th International Conference on Natural Language Processing, GoTAL 2008, Gothenburg, Sweden, August 2008. The 44 revised full papers presented together with 3 invited talks were carefully reviewed and selected from 107 submissions. The papers address all current issues in computational linguistics and monolingual and multilingual intelligent language processing - theory, methods and applications.

Trends in Parsing Technology

Trends in Parsing Technology PDF Author: Harry Bunt
Publisher: Springer Science & Business Media
ISBN: 9048193524
Category : Language Arts & Disciplines
Languages : en
Pages : 300

Book Description
Computer parsing technology, which breaks down complex linguistic structures into their constituent parts, is a key research area in the automatic processing of human language. This volume is a collection of contributions from leading researchers in the field of natural language processing technology, each of whom detail their recent work which includes new techniques as well as results. The book presents an overview of the state of the art in current research into parsing technologies, focusing on three important themes: dependency parsing, domain adaptation, and deep parsing. The technology, which has a variety of practical uses, is especially concerned with the methods, tools and software that can be used to parse automatically. Applications include extracting information from free text or speech, question answering, speech recognition and comprehension, recommender systems, machine translation, and automatic summarization. New developments in the area of parsing technology are thus widely applicable, and researchers and professionals from a number of fields will find the material here required reading. As well as the other four volumes on parsing technology in this series this book has a breadth of coverage that makes it suitable both as an overview of the field for graduate students, and as a reference for established researchers in computational linguistics, artificial intelligence, computer science, language engineering, information science, and cognitive science. It will also be of interest to designers, developers, and advanced users of natural language processing systems, including applications such as spoken dialogue, text mining, multimodal human-computer interaction, and semantic web technology.