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Empirical Methods In Natural Language Generation
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Book Synopsis Empirical Methods in Natural Language Generation by : Emiel Krahmer
Download or read book Empirical Methods in Natural Language Generation written by Emiel Krahmer and published by Springer Science & Business Media. This book was released on 2010-09-09 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural language generation (NLG) is a subfield of natural language processing (NLP) that is often characterized as the study of automatically converting non-linguistic representations (e.g., from databases or other knowledge sources) into coherent natural language text. In recent years the field has evolved substantially. Perhaps the most important new development is the current emphasis on data-oriented methods and empirical evaluation. Progress in related areas such as machine translation, dialogue system design and automatic text summarization and the resulting awareness of the importance of language generation, the increasing availability of suitable corpora in recent years, and the organization of shared tasks for NLG, where different teams of researchers develop and evaluate their algorithms on a shared, held out data set have had a considerable impact on the field, and this book offers the first comprehensive overview of recent empirically oriented NLG research.
Book Synopsis Natural Language Generation in Interactive Systems by : Amanda Stent
Download or read book Natural Language Generation in Interactive Systems written by Amanda Stent and published by Cambridge University Press. This book was released on 2014-06-12 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive overview of the state-of-the-art in natural language generation for interactive systems, with links to resources for further research.
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 535 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 Cross-Lingual Word Embeddings by : Anders Søgaard
Download or read book Cross-Lingual Word Embeddings written by Anders Søgaard and published by Springer Nature. This book was released on 2022-05-31 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: The majority of natural language processing (NLP) is English language processing, and while there is good language technology support for (standard varieties of) English, support for Albanian, Burmese, or Cebuano--and most other languages--remains limited. Being able to bridge this digital divide is important for scientific and democratic reasons but also represents an enormous growth potential. A key challenge for this to happen is learning to align basic meaning-bearing units of different languages. In this book, the authors survey and discuss recent and historical work on supervised and unsupervised learning of such alignments. Specifically, the book focuses on so-called cross-lingual word embeddings. The survey is intended to be systematic, using consistent notation and putting the available methods on comparable form, making it easy to compare wildly different approaches. In so doing, the authors establish previously unreported relations between these methods and are able to present a fast-growing literature in a very compact way. Furthermore, the authors discuss how best to evaluate cross-lingual word embedding methods and survey the resources available for students and researchers interested in this topic.
Book Synopsis Natural Language Generation by : Anja Belz
Download or read book Natural Language Generation written by Anja Belz and published by Springer. This book was released on 2011-04-02 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Third International Conference on Natural Language Generation (INLG 2004) was held from 14th to 16th July 2004 at Careys Manor, Brockenhurst, UK. Supported by the Association for Computational Linguistics Special - terest Group on Generation, the conference continued a twenty-year tradition of biennial international meetings on research into natural language generation. Recent conference venues have included Mitzpe Ramon, Israel (INLG 2000) and New York, USA (INLG 2002). It was our pleasure to invite the thriving and friendly NLG research community to the beautiful New Forest in the south of England for INLG 2004. INLG is the leading international conference in the ?eld of natural language generation. It provides a forum for the presentation and discussion of original research on all aspects of the generation of language, including psychological modelling of human language production as well as computational approaches to the automatic generation of language. This volume includes a paper by the keynote speaker, Ardi Roelofs of the Max Planck Institute for Psycholingu- tics and the F. C. Donders Centre for CognitiveNeuroimaging,18 regular papers reportingthelatestresearchresultsanddirections,and4studentpapersdescr- ing doctoral work in progress. These papers reveal a particular concentration of current research e?ort on statistical and machine learning methods, on referring expressions, and on variation in surface realisation. The papers were selected from 46 submissions from all over the world (27 from Europe, 13 from North America, 6 from elsewhere), which were subjected to a rigorous double-blind reviewing process undertaken by our hard-working programme committee.
Book Synopsis Machine Learning and Knowledge Discovery in Databases: Research Track by : Danai Koutra
Download or read book Machine Learning and Knowledge Discovery in Databases: Research Track written by Danai Koutra and published by Springer Nature. This book was released on 2023-09-16 with total page 758 pages. Available in PDF, EPUB and Kindle. Book excerpt: The multi-volume set LNAI 14169 until 14175 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, in September 2023. The 196 papers were selected from the 829 submissions for the Research Track, and 58 papers were selected from the 239 submissions for the Applied Data Science Track. The volumes are organized in topical sections as follows: Part I: Active Learning; Adversarial Machine Learning; Anomaly Detection; Applications; Bayesian Methods; Causality; Clustering. Part II: Computer Vision; Deep Learning; Fairness; Federated Learning; Few-shot learning; Generative Models; Graph Contrastive Learning. Part III: Graph Neural Networks; Graphs; Interpretability; Knowledge Graphs; Large-scale Learning. Part IV: Natural Language Processing; Neuro/Symbolic Learning; Optimization; Recommender Systems; Reinforcement Learning; Representation Learning. Part V: Robustness; Time Series; Transfer and Multitask Learning. Part VI: Applied Machine Learning; Computational Social Sciences; Finance; Hardware and Systems; Healthcare & Bioinformatics; Human-Computer Interaction; Recommendation and Information Retrieval. Part VII: Sustainability, Climate, and Environment.- Transportation & Urban Planning.- Demo.
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 AI Applications to Communications and Information Technologies by : Daniel Minoli
Download or read book AI Applications to Communications and Information Technologies written by Daniel Minoli and published by John Wiley & Sons. This book was released on 2023-12-27 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Apply the technology of the future to networking and communications. Artificial intelligence, which enables computers or computer-controlled systems to perform tasks which ordinarily require human-like intelligence and decision-making, has revolutionized computing and digital industries like few other developments in recent history. Tools like artificial neural networks, large language models, and deep learning have quickly become integral aspects of modern life. With research and development into AI technologies proceeding at lightning speeds, the potential applications of these new technologies are all but limitless. AI Applications to Communications and Information Technologies offers a cutting-edge introduction to AI applications in one particular set of disciplines. Beginning with an overview of foundational concepts in AI, it then moves through numerous possible extensions of this technology into networking and telecommunications. The result is an essential introduction for researchers and for technology undergrad/grad student alike. AI Applications to Communications and Information Technologies readers will also find: In-depth analysis of both current and evolving applications Detailed discussion of topics including generative AI, chatbots, Automatic Speech Recognition, image classification and recognition, IoT, smart buildings, network management, network security, and more An authorial team with immense experience in both research and industry AI Applications to Communications and Information Technologies is ideal for researchers, industry observers, investors, and advanced students of network communications and related fields.
Book Synopsis Natural Language Processing and Chinese Computing by : Fei Liu
Download or read book Natural Language Processing and Chinese Computing written by Fei Liu and published by Springer Nature. This book was released on 2023-10-07 with total page 897 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three-volume set constitutes the refereed proceedings of the 12th National CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2023, held in Foshan, China, during October 12–15, 2023. The 143 regular papers included in these proceedings were carefully reviewed and selected from 478 submissions. They were organized in topical sections as follows: dialogue systems; fundamentals of NLP; information extraction and knowledge graph; machine learning for NLP; machine translation and multilinguality; multimodality and explainability; NLP applications and text mining; question answering; large language models; summarization and generation; student workshop; and evaluation workshop.
Book Synopsis Deep Learning Approaches to Text Production by : Shashi Narayan
Download or read book Deep Learning Approaches to Text Production written by Shashi Narayan and published by Springer Nature. This book was released on 2022-06-01 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: Text production has many applications. It is used, for instance, to generate dialogue turns from dialogue moves, verbalise the content of knowledge bases, or generate English sentences from rich linguistic representations, such as dependency trees or abstract meaning representations. Text production is also at work in text-to-text transformations such as sentence compression, sentence fusion, paraphrasing, sentence (or text) simplification, and text summarisation. This book offers an overview of the fundamentals of neural models for text production. In particular, we elaborate on three main aspects of neural approaches to text production: how sequential decoders learn to generate adequate text, how encoders learn to produce better input representations, and how neural generators account for task-specific objectives. Indeed, each text-production task raises a slightly different challenge (e.g, how to take the dialogue context into account when producing a dialogue turn, how to detect and merge relevant information when summarising a text, or how to produce a well-formed text that correctly captures the information contained in some input data in the case of data-to-text generation). We outline the constraints specific to some of these tasks and examine how existing neural models account for them. More generally, this book considers text-to-text, meaning-to-text, and data-to-text transformations. It aims to provide the audience with a basic knowledge of neural approaches to text production and a roadmap to get them started with the related work. The book is mainly targeted at researchers, graduate students, and industrials interested in text production from different forms of inputs.
Book Synopsis Natural Language Processing and Information Systems by : Amon Rapp
Download or read book Natural Language Processing and Information Systems written by Amon Rapp and published by Springer Nature. This book was released on with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Natural Language Generation by : Ehud Reiter
Download or read book Natural Language Generation written by Ehud Reiter and published by Springer Nature. This book was released on with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Referring expression generation in context by : Fahime Same
Download or read book Referring expression generation in context written by Fahime Same and published by Language Science Press. This book was released on 2024-06-03 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reference production, often termed Referring Expression Generation (REG) in computational linguistics, encompasses two distinct tasks: (1) one-shot REG, and (2) REG-in-context. One-shot REG explores which properties of a referent offer a unique description of it. In contrast, REG-in-context asks which (anaphoric) referring expressions are optimal at various points in discourse. This book offers a series of in-depth studies of the REG-in-context task. It thoroughly explores various aspects of the task such as corpus selection, computational methods, feature analysis, and evaluation techniques. The comparative study of different corpora highlights the pivotal role of corpus choice in REG-in-context research, emphasizing its influence on all subsequent model development steps. An experimental analysis of various feature-based machine learning models reveals that those with a concise set of linguistically-informed features can rival models with more features. Furthermore, this work highlights the importance of paragraph-related concepts, an area underexplored in Natural Language Generation (NLG). The book offers a thorough evaluation of different approaches to the REG-in-context task (rule-based, feature-based, and neural end-to-end), and demonstrates that well-crafted, non-neural models are capable of matching or surpassing the performance of neural REG-in-context models. In addition, the book delves into post-hoc experiments, aimed at improving the explainability of both neural and classical REG-in-context models. It also addresses other critical topics, such as the limitations of accuracy-based evaluation metrics and the essential role of human evaluation in NLG research. These studies collectively advance our understanding of REG-in-context. They highlight the importance of selecting appropriate corpora and targeted features. They show the need for context-aware modeling and the value of a comprehensive approach to model evaluation and interpretation. This detailed analysis of REG-in-context paves the way for developing more sophisticated, linguistically-informed, and contextually appropriate NLG systems.
Book Synopsis Advances in Computational Intelligence by : Félix Castro
Download or read book Advances in Computational Intelligence written by Félix Castro and published by Springer. This book was released on 2018-12-31 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 10632 and 10633 constitutes the proceedings of the 16th Mexican International Conference on Artificial Intelligence, MICAI 2017, held in Enseneda, Mexico, in October 2017. The total of 60 papers presented in these two volumes was carefully reviewed and selected from 203 submissions. The contributions were organized in the following topical sections: Part I: neural networks; evolutionary algorithms and optimization; hybrid intelligent systems and fuzzy logic; and machine learning and data mining. Part II: natural language processing and social networks; intelligent tutoring systems and educational applications; and image processing and pattern recognition.
Book Synopsis Advanced Applications of Generative AI and Natural Language Processing Models by : Obaid, Ahmed J.
Download or read book Advanced Applications of Generative AI and Natural Language Processing Models written by Obaid, Ahmed J. and published by IGI Global. This book was released on 2023-12-21 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rapid advancements in Artificial Intelligence (AI), specifically in Natural Language Processing (NLP) and Generative AI, pose a challenge for academic scholars. Staying current with the latest techniques and applications in these fields is difficult due to their dynamic nature, while the lack of comprehensive resources hinders scholars' ability to effectively utilize these technologies. Advanced Applications of Generative AI and Natural Language Processing Models offers an effective solution to address these challenges. This comprehensive book delves into cutting-edge developments in NLP and Generative AI. It provides insights into the functioning of these technologies, their benefits, and associated challenges. Targeting students, researchers, and professionals in AI, NLP, and computer science, this book serves as a vital reference for deepening knowledge of advanced NLP techniques and staying updated on the latest advancements in generative AI. By providing real-world examples and practical applications, scholars can apply their learnings to solve complex problems across various domains. Embracing Advanced Applications of Generative AI and Natural Language Processing Modelsequips academic scholars with the necessary knowledge and insights to explore innovative applications and unleash the full potential of generative AI and NLP models for effective problem-solving.
Book Synopsis Chinese Computational Linguistics by : Maosong Sun
Download or read book Chinese Computational Linguistics written by Maosong Sun and published by Springer Nature. This book was released on 2022-10-06 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 21st China National Conference on Computational Linguistics, CCL 2022, held in Nanchang, China, in October 2022. The 22 full English-language papers in this volume were carefully reviewed and selected from 293 Chinese and English submissions. The conference papers are categorized into the following topical sub-headings: Linguistics and Cognitive Science; Fundamental Theory and Methods of Computational Linguistics; Information Retrieval, Dialogue and Question Answering; Text Generation and Summarization; Knowledge Graph and Information Extraction; Machine Translation and Multilingual Information Processing; Minority Language Information Processing; Language Resource and Evaluation; NLP Applications.
Book Synopsis Advanced Intelligent Computing Technology and Applications by : De-Shuang Huang
Download or read book Advanced Intelligent Computing Technology and Applications written by De-Shuang Huang and published by Springer Nature. This book was released on with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt:
