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.

Download or read book Semi supervised Methods for Out of domain Dependency Parsing written by Juntao Yu and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Semi Supervised Learning and Domain Adaptation in Natural Language Processing written by Anders Søgaard and published by Springer Nature. This book was released on 2022-05-31 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces basic supervised learning algorithms applicable to natural language processing (NLP) and shows how the performance of these algorithms can often be improved by exploiting the marginal distribution of large amounts of unlabeled data. One reason for that is data sparsity, i.e., the limited amounts of data we have available in NLP. However, in most real-world NLP applications our labeled data is also heavily biased. This book introduces extensions of supervised learning algorithms to cope with data sparsity and different kinds of sampling bias. This book is intended to be both readable by first-year students and interesting to the expert audience. My intention was to introduce what is necessary to appreciate the major challenges we face in contemporary NLP related to data sparsity and sampling bias, without wasting too much time on details about supervised learning algorithms or particular NLP applications. I use text classification, part-of-speech tagging, and dependency parsing as running examples, and limit myself to a small set of cardinal learning algorithms. I have worried less about theoretical guarantees ("this algorithm never does too badly") than about useful rules of thumb ("in this case this algorithm may perform really well"). In NLP, data is so noisy, biased, and non-stationary that few theoretical guarantees can be established and we are typically left with our gut feelings and a catalogue of crazy ideas. I hope this book will provide its readers with both. Throughout the book we include snippets of Python code and empirical evaluations, when relevant.

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

Download or read book Advances in Discriminative Dependency Parsing written by Terry Y. Koo and published by . This book was released on 2010 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: Achieving a greater understanding of natural language syntax and parsing is a critical step in producing useful natural language processing systems. In this thesis, we focus on the formalism of dependency grammar as it allows one to model important head modifier relationships with a minimum of extraneous structure. Recent research in dependency parsing has highlighted the discriminative structured prediction framework (McDonald et al., 2005a; Carreras, 2007; Suzuki et al., 2009), which is characterized by two advantages: first, the availability of powerful discriminative learning algorithms like log-linear and max-margin models (Lafferty et al., 2001; Taskar et al., 2003), and second, the ability to use arbitrarily-defined feature representations. This thesis explores three advances in the field of discriminative dependency parsing. First, we show that the classic Matrix-Tree Theorem (Kirchhoff, 1847; Tutte, 1984) can be applied to the problem of non-projective dependency parsing, enabling both log-linear and max-margin parameter estimation in this setting. Second, we present novel third-order dependency parsing algorithms that extend the amount of context available to discriminative parsers while retaining computational complexity equivalent to existing second-order parsers. Finally, we describe a simple but effective method for augmenting the features of a dependency parser with information derived from standard clustering algorithms; our semi-supervised approach is able to deliver consistent benefits regardless of the amount of available training data.

Download or read book Advances in Natural Language Processing written by Hrafn Loftsson and published by Springer Science & Business Media. This book was released on 2010-07-30 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 7th International Conference on Advances in Natural Language Processing held in Reykjavik, Iceland, in August 2010.

Download or read book Towards Less Supervision in Dependency Parsing written by Seyedabolghasem Mirroshandel and published by . This book was released on 2015 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic parsing is one of the most attractive research areas in natural language processing. Current successful probabilistic parsers require large treebanks which are difficult, time consuming, and expensive to produce. Therefore, we focused our attention on less-supervised approaches. We suggested two categories of solution: active learning and semi-supervised algorithm. Active learning strategies allow one to select the most informative samples for annotation. Most existing active learning strategies for parsing rely on selecting uncertain sentences for annotation. We show in our research, on four different languages (French, English, Persian, and Arabic), that selecting full sentences is not an optimal solution and propose a way to select only subparts of sentences. As our experiments have shown, some parts of the sentences do not contain any useful information for training a parser, and focusing on uncertain subparts of the sentences is a more effective solution in active learning.

Download or read book International Conference on Digital Libraries ICDL 2016 written by Shantanu Ganguly and published by The Energy and Resources Institute (TERI). This book was released on 2016-12-14 with total page 1072 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ICDL Conferences are recognized as one of the most important platforms in the world where noted experts share their experiences. Many DL experts have contributed thought-provoking papers in ICDL 2016. These important papers are reviewed and conceptualized into ICDL on di_ erent areas of DL proceedings. The Proceedings have two volumes and over 700 pages.

Download or read book Natural Language Processing and Chinese Computing written by Juanzi Li and published by Springer. This book was released on 2015-10-07 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 4th CCF Conference, NLPCC 2015, held in Nanchang, China, in October 2015. The 35 revised full papers presented together with 22 short papers were carefully reviewed and selected from 238 submissions. The papers are organized in topical sections on fundamentals on language computing; applications on language computing; NLP for search technology and ads; web mining; knowledge acquisition and information extraction.

Download or read book Neural Information Processing written by Akira Hirose and published by Springer. This book was released on 2016-09-30 with total page 646 pages. Available in PDF, EPUB and Kindle. Book excerpt: The four volume set LNCS 9947, LNCS 9948, LNCS 9949, and LNCS 9950 constitutes the proceedings of the 23rd International Conference on Neural Information Processing, ICONIP 2016, held in Kyoto, Japan, in October 2016. The 296 full papers presented were carefully reviewed and selected from 431 submissions. The 4 volumes are organized in topical sections on deep and reinforcement learning; big data analysis; neural data analysis; robotics and control; bio-inspired/energy efficient information processing; whole brain architecture; neurodynamics; bioinformatics; biomedical engineering; data mining and cybersecurity workshop; machine learning; neuromorphic hardware; sensory perception; pattern recognition; social networks; brain-machine interface; computer vision; time series analysis; data-driven approach for extracting latent features; topological and graph based clustering methods; computational intelligence; data mining; deep neural networks; computational and cognitive neurosciences; theory and algorithms.

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

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.

Download or read book Natural Language Processing and Chinese Computing written by Jie Tang and published by Springer Nature. This book was released on 2019-09-30 with total page 850 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set of LNAI 11838 and LNAI 11839 constitutes the refereed proceedings of the 8th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2019, held in Dunhuang, China, in October 2019. The 85 full papers and 56 short papers presented were carefully reviewed and selected from 492 submissions. They are organized in the following topical sections: Conversational Bot/QA/IR; Knowledge graph/IE; Machine Learning for NLP; Machine Translation; NLP Applications; NLP for Social Network; NLP Fundamentals; Text Mining; Short Papers; Explainable AI Workshop; Student Workshop: Evaluation Workshop.

Download or read book Language Technologies for the Challenges of the Digital Age written by Georg Rehm and published by Springer. This book was released on 2018-01-05 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access volume constitutes the refereed proceedings of the 27th biennial conference of the German Society for Computational Linguistics and Language Technology, GSCL 2017, held in Berlin, Germany, in September 2017, which focused on language technologies for the digital age. The 16 full papers and 10 short papers included in the proceedings were carefully selected from 36 submissions. Topics covered include text processing of the German language, online media and online content, semantics and reasoning, sentiment analysis, and semantic web description languages.

Download or read book Natural Language Understanding and Intelligent Applications written by Chin-Yew Lin and published by Springer. This book was released on 2016-11-30 with total page 963 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the joint refereed proceedings of the 5th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2016, and the 24th International Conference on Computer Processing of Oriental Languages, ICCPOL 2016, held in Kunming, China, in December 2016. The 48 revised full papers presented together with 41 short papers were carefully reviewed and selected from 216 submissions. The papers cover fundamental research in language computing, multi-lingual access, web mining/text mining, machine learning for NLP, knowledge graph, NLP for social network, as well as applications in language computing.

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.

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.