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Dependency Parsing
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Book Synopsis Inductive Dependency Parsing by : Joakim Nivre
Download or read book Inductive Dependency Parsing written by Joakim Nivre and published by Springer Science & Business Media. This book was released on 2006-08-05 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Dependency Parsing by : Sandra Kubler
Download or read book Dependency Parsing written by Sandra Kubler and published by Springer Nature. This book was released on 2022-05-31 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Dependency Parsing by : Sandra Kübler
Download or read book Dependency Parsing written by Sandra Kübler and published by Morgan & Claypool Publishers. This book was released on 2009 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Natural Language Processing: Python and NLTK by : Nitin Hardeniya
Download or read book Natural Language Processing: Python and NLTK written by Nitin Hardeniya and published by Packt Publishing Ltd. This book was released on 2016-11-22 with total page 687 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to build expert NLP and machine learning projects using NLTK and other Python libraries About This Book Break text down into its component parts for spelling correction, feature extraction, and phrase transformation Work through NLP concepts with simple and easy-to-follow programming recipes Gain insights into the current and budding research topics of NLP Who This Book Is For If you are an NLP or machine learning enthusiast and an intermediate Python programmer who wants to quickly master NLTK for natural language processing, then this Learning Path will do you a lot of good. Students of linguistics and semantic/sentiment analysis professionals will find it invaluable. What You Will Learn The scope of natural language complexity and how they are processed by machines Clean and wrangle text using tokenization and chunking to help you process data better Tokenize text into sentences and sentences into words Classify text and perform sentiment analysis Implement string matching algorithms and normalization techniques Understand and implement the concepts of information retrieval and text summarization Find out how to implement various NLP tasks in Python In Detail Natural Language Processing is a field of computational linguistics and artificial intelligence that deals with human-computer interaction. It provides a seamless interaction between computers and human beings and gives computers the ability to understand human speech with the help of machine learning. The number of human-computer interaction instances are increasing so it's becoming imperative that computers comprehend all major natural languages. The first NLTK Essentials module is an introduction on how to build systems around NLP, with a focus on how to create a customized tokenizer and parser from scratch. You will learn essential concepts of NLP, be given practical insight into open source tool and libraries available in Python, shown how to analyze social media sites, and be given tools to deal with large scale text. This module also provides a workaround using some of the amazing capabilities of Python libraries such as NLTK, scikit-learn, pandas, and NumPy. The second Python 3 Text Processing with NLTK 3 Cookbook module teaches you the essential techniques of text and language processing with simple, straightforward examples. This includes organizing text corpora, creating your own custom corpus, text classification with a focus on sentiment analysis, and distributed text processing methods. The third Mastering Natural Language Processing with Python module will help you become an expert and assist you in creating your own NLP projects using NLTK. You will be guided through model development with machine learning tools, shown how to create training data, and given insight into the best practices for designing and building NLP-based applications using Python. This Learning Path combines some of the best that Packt has to offer in one complete, curated package and is designed to help you quickly learn text processing with Python and NLTK. It includes content from the following Packt products: NTLK essentials by Nitin Hardeniya Python 3 Text Processing with NLTK 3 Cookbook by Jacob Perkins Mastering Natural Language Processing with Python by Deepti Chopra, Nisheeth Joshi, and Iti Mathur Style and approach This comprehensive course creates a smooth learning path that teaches you how to get started with Natural Language Processing using Python and NLTK. You'll learn to create effective NLP and machine learning projects using Python and NLTK.
Book Synopsis Semi-Supervised Dependency Parsing by : Wenliang Chen
Download or read book Semi-Supervised Dependency Parsing written by Wenliang Chen and published by Springer. This book was released on 2015-07-16 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Trends in Parsing Technology by : Harry Bunt
Download or read book Trends in Parsing Technology written by Harry Bunt and published by Springer Science & Business Media. This book was released on 2010-10-06 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Security and Intelligent Information Systems by : Pascal Bouvry
Download or read book Security and Intelligent Information Systems written by Pascal Bouvry and published by Springer. This book was released on 2012-02-02 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the Joint Meeting of the 2nd Luxembourg-Polish Symposium on Security and Trust and the 19th International Conference Intelligent Information Systems, held as International Joint Confererence on Security and Intelligent Information Systems, SIIS 2011, in Warsaw, Poland, in June 2011. The 29 revised full papers presented together with 2 invited lectures were carefully reviewed and selected from 60 initial submissions during two rounds of selection and improvement. The papers are organized in the following three thematic tracks: security and trust, data mining and machine learning, and natural language processing.
Book Synopsis SOFSEM 2015: Theory and Practice of Computer Science by : Giuseppe Italiano
Download or read book SOFSEM 2015: Theory and Practice of Computer Science written by Giuseppe Italiano and published by Springer. This book was released on 2015-01-14 with total page 631 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 41st International Conference on Current Trends in Theory and Practice of Computer Science held in Pec pod Sněžkou, Czech Republic, during January 24-29, 2015. The book features 8 invited talks and 42 regular papers which were carefully reviewed and selected from 101 submissions. The papers are organized in topical sections named: foundations of computer science; software and Web engineering; data, information, and knowledge engineering; and cryptography, security, and verification.
Book Synopsis Information Retrieval Technology by : Hang Li
Download or read book Information Retrieval Technology written by Hang Li and published by Springer Science & Business Media. This book was released on 2008-05-29 with total page 701 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the 4th Asia Information Retrieval Symposium, AIRS 2008, held in Harbin, China, in May 2008. The 39 revised full papers and 43 revised poster papers presented were carefully reviewed and selected from 144 submissions. All current issues in information retrieval are addressed: applications, systems, technologies and theoretical aspects of information retrieval in text, audio, image, video and multi-media data. The papers are organized in topical sections on IR models image retrieval, text classification, chinese language processing, text processing, application of IR, machine learning, taxonomy, IR methods, information extraction, summarization, multimedia, Web IR, and text clustering.
Book Synopsis Parsing Schemata for Practical Text Analysis by : Carlos G¢mez Rodr¡guez
Download or read book Parsing Schemata for Practical Text Analysis written by Carlos G¢mez Rodr¡guez and published by World Scientific. This book was released on 2010 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents a wide range of recent research results about parsing schemata, introducing formal frameworks and theoretical results while keeping a constant focus on applicability to practical parsing problems. The first part includes a general introduction to the parsing schemata formalism that contains the basic notions needed to understand the rest of the parts. Thus, this compendium can be used as an introduction to natural language parsing, allowing postgraduate students not only to get a solid grasp of the fundamental concepts underlying parsing algorithms, but also an understanding of the latest developments and challenges in the field. Researchers in computational linguistics will find novel results where parsing schemata are applied to current problems that are being actively researched in the computational linguistics community (like dependency parsing, robust parsing, or the treatment of non-projective linguistics phenomena). This book not only explains these results in a more detailed, comprehensive and self-contained way, and highlights the relations between them, but also includes new contributions that have not been presented.
Book Synopsis Information, Computer and Application Engineering by : Hsiang-Chuan Liu
Download or read book Information, Computer and Application Engineering written by Hsiang-Chuan Liu and published by CRC Press. This book was released on 2018-06-12 with total page 1146 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceedings volume brings together peer-reviewed papers presented at the International Conference on Information Technology and Computer Application Engineering, held 10-11 December 2014, in Hong Kong, China. Specific topics under consideration include Computational Intelligence, Computer Science and its Applications, Intelligent Information Processing and Knowledge Engineering, Intelligent Networks and Instruments, Multimedia Signal Processing and Analysis, Intelligent Computer-Aided Design Systems and other related topics. This book provides readers a state-of-the-art survey of recent innovations and research worldwide in Information Technology and Computer Application Engineering, in so-doing furthering the development and growth of these research fields, strengthening international academic cooperation and communication, and promoting the fruitful exchange of research ideas. This volume will be of interest to professionals and academics alike, serving as a broad overview of the latest advances in the dynamic field of Information Technology and Computer Application Engineering.
Book Synopsis Introduction to Natural Language Processing by : Jacob Eisenstein
Download or read book Introduction to Natural Language Processing written by Jacob Eisenstein and published by MIT Press. This book was released on 2019-10-01 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: A survey of computational methods for understanding, generating, and manipulating human language, which offers a synthesis of classical representations and algorithms with contemporary machine learning techniques. This textbook provides a technical perspective on natural language processing—methods for building computer software that understands, generates, and manipulates human language. It emphasizes contemporary data-driven approaches, focusing on techniques from supervised and unsupervised machine learning. The first section establishes a foundation in machine learning by building a set of tools that will be used throughout the book and applying them to word-based textual analysis. The second section introduces structured representations of language, including sequences, trees, and graphs. The third section explores different approaches to the representation and analysis of linguistic meaning, ranging from formal logic to neural word embeddings. The final section offers chapter-length treatments of three transformative applications of natural language processing: information extraction, machine translation, and text generation. End-of-chapter exercises include both paper-and-pencil analysis and software implementation. The text synthesizes and distills a broad and diverse research literature, linking contemporary machine learning techniques with the field's linguistic and computational foundations. It is suitable for use in advanced undergraduate and graduate-level courses and as a reference for software engineers and data scientists. Readers should have a background in computer programming and college-level mathematics. After mastering the material presented, students will have the technical skill to build and analyze novel natural language processing systems and to understand the latest research in the field.
Book Synopsis Advances in Natural Language Processing by : Bengt Nordström
Download or read book Advances in Natural Language Processing written by Bengt Nordström and published by Springer Science & Business Media. This book was released on 2008-08-13 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Text, Speech, and Dialogue by : Ivan Habernal
Download or read book Text, Speech, and Dialogue written by Ivan Habernal and published by Springer. This book was released on 2013-08-17 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 16th International Conference on Text, Speech and Dialogue, TSD 2013, held in Pilsen, Czech Republic, in September 2013. The 65 papers presented together with 5 invited talks were carefully reviewed and selected from 148 submissions. The main topics of this year's conference was corpora, texts and transcription, speech analysis, recognition and synthesis, and their intertwining within NL dialogue systems. The topics also included speech recognition, corpora and language resources, speech and spoken language generation, tagging, classification and parsing of text and speech, semantic processing of text and speech, integrating applications of text and speech processing, as well as automatic dialogue systems, and multimodal techniques and modelling.
Book Synopsis Evaluation of Natural Language and Speech Tool for Italian by : Bernardo Magnini
Download or read book Evaluation of Natural Language and Speech Tool for Italian written by Bernardo Magnini and published by Springer. This book was released on 2013-01-03 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: EVALITA (http://www.evalita.it/) is the reference evaluation campaign of both Natural Language Processing and Speech Technologies for the Italian language. The objective of the shared tasks proposed at EVALITA is to promote the development of language technologies for Italian, providing a common framework where different systems and approaches can be evaluated and compared in a consistent manner. This volume collects the final and extended contributions presented at EVALITA 2011, the third edition of the evaluation campaign. The 36 revised full papers were carefully reviewed and selected from a total of 87 submissions. The papers are organized in topical sections roughly corresponding to evaluation tasks: parsing - dependency parsing track, parsing - constituency parsing track, domain adaptation for dependency parsing, named entity recognition on transcribed broadcast news, cross-document coreference resolution of named person entities, anaphora resolution, supersense tagging, frame labeling over italian texts, lemmatisation, automatic speech recognition - large vocabulary transcription, forced alignment on spontaneous speech.
Book Synopsis Artificial Intelligence and Computational Intelligence by : Hepu Deng
Download or read book Artificial Intelligence and Computational Intelligence written by Hepu Deng and published by Springer. This book was released on 2011-09-25 with total page 693 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three-volume proceedings contains revised selected papers from the Second International Conference on Artificial Intelligence and Computational Intelligence, AICI 2011, held in Taiyuan, China, in September 2011. The total of 265 high-quality papers presented were carefully reviewed and selected from 1073 submissions. The topics of Part III covered are: machine vision; natural language processing; nature computation; neural computation; neural networks; particle swarm optimization; pattern recognition; rough set theory; and support vector machine.
Book Synopsis Natural Language Processing and Computational Linguistics by : Bhargav Srinivasa-Desikan
Download or read book Natural Language Processing and Computational Linguistics written by Bhargav Srinivasa-Desikan and published by Packt Publishing Ltd. This book was released on 2018-06-29 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Work with Python and powerful open source tools such as Gensim and spaCy to perform modern text analysis, natural language processing, and computational linguistics algorithms. Key Features Discover the open source Python text analysis ecosystem, using spaCy, Gensim, scikit-learn, and Keras Hands-on text analysis with Python, featuring natural language processing and computational linguistics algorithms Learn deep learning techniques for text analysis Book Description Modern text analysis is now very accessible using Python and open source tools, so discover how you can now perform modern text analysis in this era of textual data. This book shows you how to use natural language processing, and computational linguistics algorithms, to make inferences and gain insights about data you have. These algorithms are based on statistical machine learning and artificial intelligence techniques. The tools to work with these algorithms are available to you right now - with Python, and tools like Gensim and spaCy. You'll start by learning about data cleaning, and then how to perform computational linguistics from first concepts. You're then ready to explore the more sophisticated areas of statistical NLP and deep learning using Python, with realistic language and text samples. You'll learn to tag, parse, and model text using the best tools. You'll gain hands-on knowledge of the best frameworks to use, and you'll know when to choose a tool like Gensim for topic models, and when to work with Keras for deep learning. This book balances theory and practical hands-on examples, so you can learn about and conduct your own natural language processing projects and computational linguistics. You'll discover the rich ecosystem of Python tools you have available to conduct NLP - and enter the interesting world of modern text analysis. What you will learn Why text analysis is important in our modern age Understand NLP terminology and get to know the Python tools and datasets Learn how to pre-process and clean textual data Convert textual data into vector space representations Using spaCy to process text Train your own NLP models for computational linguistics Use statistical learning and Topic Modeling algorithms for text, using Gensim and scikit-learn Employ deep learning techniques for text analysis using Keras Who this book is for This book is for you if you want to dive in, hands-first, into the interesting world of text analysis and NLP, and you're ready to work with the rich Python ecosystem of tools and datasets waiting for you!
