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 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 Statistical Language and Speech Processing written by Pavel Král and published by Springer. This book was released on 2016-09-20 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 4th International Conference on Statistical Language and Speech Processing, SLSP 2016, held in Pilsen, Czech Republic, in October 2016. The 11 full papers presented together with two invited talks were carefully reviewed and selected from 38 submissions. The papers cover topics such as anaphora and coreference resolution; authorship identification, plagiarism and spam filtering; computer-aided translation; corpora and language resources; data mining and semantic web; information extraction; information retrieval; knowledge representation and ontologies; lexicons and dictionaries; machine translation; multimodal technologies; natural language understanding; neural representation of speech and language; opinion mining and sentiment analysis; parsing; part-of-speech tagging; question and answering systems; semantic role labeling; speaker identification and verification; speech and language generation; speech recognition; speech synthesis; speech transcription; speech correction; spoken dialogue systems; term extraction; text categorization; test summarization; user modeling.
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 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 Deep Learning and Linguistic Representation written by Shalom Lappin and published by CRC Press. This book was released on 2021-04-27 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: The application of deep learning methods to problems in natural language processing has generated significant progress across a wide range of natural language processing tasks. For some of these applications, deep learning models now approach or surpass human performance. While the success of this approach has transformed the engineering methods of machine learning in artificial intelligence, the significance of these achievements for the modelling of human learning and representation remains unclear. Deep Learning and Linguistic Representation looks at the application of a variety of deep learning systems to several cognitively interesting NLP tasks. It also considers the extent to which this work illuminates our understanding of the way in which humans acquire and represent linguistic knowledge. Key Features: combines an introduction to deep learning in AI and NLP with current research on Deep Neural Networks in computational linguistics. is self-contained and suitable for teaching in computer science, AI, and cognitive science courses; it does not assume extensive technical training in these areas. provides a compact guide to work on state of the art systems that are producing a revolution across a range of difficult natural language tasks.
Download or read book Handbook of Natural Language Processing written by Nitin Indurkhya and published by CRC Press. This book was released on 2010-02-22 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Natural Language Processing, Second Edition presents practical tools and techniques for implementing natural language processing in computer systems. Along with removing outdated material, this edition updates every chapter and expands the content to include emerging areas, such as sentiment analysis.New to the Second EditionGreater
Download or read book Advances in Natural Language Processing written by Aarne Ranta and published by Springer. This book was released on 2008-08-28 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.
Download or read book Proceedings of International Conference on Data Science and Applications written by Mukesh Saraswat and published by Springer Nature. This book was released on 2023-02-16 with total page 946 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers outstanding papers presented at the International Conference on Data Science and Applications (ICDSA 2022), organized by Soft Computing Research Society (SCRS) and Jadavpur University, Kolkata, India, from 26 to 27 March 2022. It covers theoretical and empirical developments in various areas of big data analytics, big data technologies, decision tree learning, wireless communication, wireless sensor networking, bioinformatics and systems, artificial neural networks, deep learning, genetic algorithms, data mining, fuzzy logic, optimization algorithms, image processing, computational intelligence in civil engineering, and creative 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 Language Networks written by Richard A. Hudson and published by Oxford University Press. This book was released on 2007 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Networks of Language" will interest all those concerned with the acquisition and everyday operations of language, in particular scholars and advanced students in linguistics, psychology, and cognitive
Download or read book Foundation Models for Natural Language Processing written by Gerhard Paaß and published by Springer Nature. This book was released on 2023-05-23 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book provides a comprehensive overview of the state of the art in research and applications of Foundation Models and is intended for readers familiar with basic Natural Language Processing (NLP) concepts. Over the recent years, a revolutionary new paradigm has been developed for training models for NLP. These models are first pre-trained on large collections of text documents to acquire general syntactic knowledge and semantic information. Then, they are fine-tuned for specific tasks, which they can often solve with superhuman accuracy. When the models are large enough, they can be instructed by prompts to solve new tasks without any fine-tuning. Moreover, they can be applied to a wide range of different media and problem domains, ranging from image and video processing to robot control learning. Because they provide a blueprint for solving many tasks in artificial intelligence, they have been called Foundation Models. After a brief introduction to basic NLP models the main pre-trained language models BERT, GPT and sequence-to-sequence transformer are described, as well as the concepts of self-attention and context-sensitive embedding. Then, different approaches to improving these models are discussed, such as expanding the pre-training criteria, increasing the length of input texts, or including extra knowledge. An overview of the best-performing models for about twenty application areas is then presented, e.g., question answering, translation, story generation, dialog systems, generating images from text, etc. For each application area, the strengths and weaknesses of current models are discussed, and an outlook on further developments is given. In addition, links are provided to freely available program code. A concluding chapter summarizes the economic opportunities, mitigation of risks, and potential developments of AI.
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 The Semantic Web written by Karl Aberer and published by Springer Science & Business Media. This book was released on 2007-10-27 with total page 999 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the joined 6th International Semantic Web Conference, ISWC 2007, and the 2nd Asian Semantic Web Conference, ASWC 2007. The papers address all current issues in the field of the semantic Web, ranging from theoretical and foundational aspects to various applied topics such as management of semantic Web data, ontologies, semantic Web architecture, social semantic Web, as well as applications of the semantic Web.
Download or read book Web Information Systems and Technologies written by José Cordeiro and published by Springer. This book was released on 2010-03-14 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains a selection of the best papers from WEBIST 2009 (the 5th Int- national Conference on Web Information Systems and Technologies), held in Lisbon, Portugal, in 2009, organized by the Institute for Systems and Technologies of Inf- mation, Control and Communication (INSTICC), in collaboration with ACM SIGMIS and co-sponsored by the Workflow Management Coalition (WFMC). The purpose of the WEBIST series of conferences is to bring together researchers, engineers and practitioners interested in the technological advances and business applications of Web-based information systems. The conference has four main tracks, covering different aspects of Web information systems, including Internet Techn- ogy, Web Interfaces and Applications, Society, e-Communities, e-Business and e-Government. WEBIST 2009 received 203 paper submissions from 47 countries on all con- nents. A double-blind review process was enforced, with the help of more than 150 experts from the International Program Committee; each of them specialized in one of the main conference topic areas. After reviewing, 28 papers were selected to be published and presented as full papers and 44 additional papers, describing work-- progress, published and presented as short papers. Furthermore, 35 papers were p- sented as posters. The full-paper acceptance ratio was 13%, and the total oral paper acceptance ratio was 36%. Therefore, we hope that you find the papers included in this book interesting, and we trust they may represent a helpful reference for all those who need to address any of the research areas mentioned above. January 2010 José Cordeiro Joaquim Filipe
Download or read book Text Analysis Pipelines written by Henning Wachsmuth and published by Springer. This book was released on 2015-12-02 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph proposes a comprehensive and fully automatic approach to designing text analysis pipelines for arbitrary information needs that are optimal in terms of run-time efficiency and that robustly mine relevant information from text of any kind. Based on state-of-the-art techniques from machine learning and other areas of artificial intelligence, novel pipeline construction and execution algorithms are developed and implemented in prototypical software. Formal analyses of the algorithms and extensive empirical experiments underline that the proposed approach represents an essential step towards the ad-hoc use of text mining in web search and big data analytics. Both web search and big data analytics aim to fulfill peoples’ needs for information in an adhoc manner. The information sought for is often hidden in large amounts of natural language text. Instead of simply returning links to potentially relevant texts, leading search and analytics engines have started to directly mine relevant information from the texts. To this end, they execute text analysis pipelines that may consist of several complex information-extraction and text-classification stages. Due to practical requirements of efficiency and robustness, however, the use of text mining has so far been limited to anticipated information needs that can be fulfilled with rather simple, manually constructed pipelines.
Download or read book Similar Languages Varieties and Dialects written by Marcos Zampieri and published by Cambridge University Press. This book was released on 2021-04-30 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt:
