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Hierarchical Joint Learning For Natural Language Generation
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Book Synopsis Hierarchical Joint Learning for Natural Language Generation by : Nina Dethlefs
Download or read book Hierarchical Joint Learning for Natural Language Generation written by Nina Dethlefs and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural Language Generation NLG systems in interactive settings often face a multitude of choices, given that the communicative effect of each utterance they generate depends crucially on the interplay between its situational circumstances, addressee and interaction history. This is particularly true in interactive and situated settings. Traditionally, the generation process has been divided into distinct stages of decision making, e.g. content selection, utterance planning and surface realization. However, this sequential model does not account for the interdependencies that exist among these stages, which in practice can
Book Synopsis Reinforcement Learning for Adaptive Dialogue Systems by : Verena Rieser
Download or read book Reinforcement Learning for Adaptive Dialogue Systems written by Verena Rieser and published by Springer Science & Business Media. This book was released on 2011-11-23 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past decade has seen a revolution in the field of spoken dialogue systems. As in other areas of Computer Science and Artificial Intelligence, data-driven methods are now being used to drive new methodologies for system development and evaluation. This book is a unique contribution to that ongoing change. A new methodology for developing spoken dialogue systems is described in detail. The journey starts and ends with human behaviour in interaction, and explores methods for learning from the data, for building simulation environments for training and testing systems, and for evaluating the results. The detailed material covers: Spoken and Multimodal dialogue systems, Wizard-of-Oz data collection, User Simulation methods, Reinforcement Learning, and Evaluation methodologies. The book is a research guide for students and researchers with a background in Computer Science, AI, or Machine Learning. It navigates through a detailed case study in data-driven methods for development and evaluation of spoken dialogue systems. Common challenges associated with this approach are discussed and example solutions are provided. This work provides insights, lessons, and inspiration for future research and development – not only for spoken dialogue systems in particular, but for data-driven approaches to human-machine interaction in general.
Book Synopsis Efficient Frequent Subtree Mining Beyond Forests by : P. Welke
Download or read book Efficient Frequent Subtree Mining Beyond Forests written by P. Welke and published by IOS Press. This book was released on 2020-06-02 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: A common paradigm in distance-based learning is to embed the instance space into a feature space equipped with a metric and define the dissimilarity between instances by the distance of their images in the feature space. Frequent connected subgraphs are sometimes used to define such feature spaces if the instances are graphs, but identifying the set of frequent connected subgraphs and subsequently computing embeddings for graph instances is computationally intractable. As a result, existing frequent subgraph mining algorithms either restrict the structural complexity of the instance graphs or require exponential delay between the output of subsequent patterns, meaning that distance-based learners lack an efficient way to operate on arbitrary graph data. This book presents a mining system that gives up the demand on the completeness of the pattern set, and instead guarantees a polynomial delay between subsequent patterns. To complement this, efficient methods devised to compute the embedding of arbitrary graphs into the Hamming space spanned by the pattern set are described. As a result, a system is proposed that allows the efficient application of distance-based learning methods to arbitrary graph databases. In addition to an introduction and conclusion, the book is divided into chapters covering: preliminaries; related work; probabilistic frequent subtrees; boosted probabilistic frequent subtrees; and fast computation, with a further two chapters on Hamiltonian path for cactus graphs and Poisson binomial distribution.
Book Synopsis Knowledge Representation and Inductive Reasoning Using Conditional Logic and Sets of Ranking Functions by : S. Kutsch
Download or read book Knowledge Representation and Inductive Reasoning Using Conditional Logic and Sets of Ranking Functions written by S. Kutsch and published by IOS Press. This book was released on 2021-02-09 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: A core problem in Artificial Intelligence is the modeling of human reasoning. Classic-logical approaches are too rigid for this task, as deductive inference yielding logically correct results is not appropriate in situations where conclusions must be drawn based on the incomplete or uncertain knowledge present in virtually all real world scenarios. Since there are no mathematically precise and generally accepted definitions for the notions of plausible or rational, the question of what a knowledge base consisting of uncertain rules entails has long been an issue in the area of knowledge representation and reasoning. Different nonmonotonic logics and various semantic frameworks and axiom systems have been developed to address this question. The main theme of this book, Knowledge Representation and Inductive Reasoning using Conditional Logic and Sets of Ranking Functions, is inductive reasoning from conditional knowledge bases. Using ordinal conditional functions as ranking models for conditional knowledge bases, the author studies inferences induced by individual ranking models as well as by sets of ranking models. He elaborates in detail the interrelationships among the resulting inference relations and shows their formal properties with respect to established inference axioms. Based on the introduction of a novel classification scheme for conditionals, he also addresses the question of how to realize and implement the entailment relations obtained. In this work, “Steven Kutsch convincingly presents his ideas, provides illustrating examples for them, rigorously defines the introduced concepts, formally proves all technical results, and fully implements every newly introduced inference method in an advanced Java library (...). He significantly advances the state of the art in this field.” – Prof. Dr. Christoph Beierle of the FernUniversität in Hagen
Book Synopsis Word Embeddings: Reliability & Semantic Change by : J. Hellrich
Download or read book Word Embeddings: Reliability & Semantic Change written by J. Hellrich and published by IOS Press. This book was released on 2019-08-08 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: Word embeddings are a form of distributional semantics increasingly popular for investigating lexical semantic change. However, typical training algorithms are probabilistic, limiting their reliability and the reproducibility of studies. Johannes Hellrich investigated this problem both empirically and theoretically and found some variants of SVD-based algorithms to be unaffected. Furthermore, he created the JeSemE website to make word embedding based diachronic research more accessible. It provides information on changes in word denotation and emotional connotation in five diachronic corpora. Finally, the author conducted two case studies on the applicability of these methods by investigating the historical understanding of electricity as well as words connected to Romanticism. They showed the high potential of distributional semantics for further applications in the digital humanities.
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.
Download or read book Flexible Workflows written by L. Grumbach and published by IOS Press. This book was released on 2023-07-07 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Traditional workflow management systems support the fulfillment of business tasks by providing guidance along a predefined workflow model. Due to the shift from mass production to customization, flexibility has become important in recent decades, but the various approaches to workflow flexibility either require extensive knowledge acquisition and modeling, or active intervention during execution. Pursuing flexibility by deviation compensates for these disadvantages by allowing alternative paths of execution at run time without requiring adaptation to the workflow model. This work, Flexible Workflows: A Constraint- and Case-Based Approach, proposes a novel approach to flexibility by deviation, the aim being to provide support during the execution of a workflow by suggesting items based on predefined strategies or experiential knowledge, even in case of deviations. The concepts combine two familiar methods from the field of AI - constraint satisfaction problem solving, and process-oriented case-based reasoning. The combined model increases the capacity for flexibility. The experimental evaluation of the approach consisted of a simulation involving several types of participant in the domain of deficiency management in construction. The book contains 7 chapters covering foundations; domains and potentials; prerequisites; constraint based workflow engine; case based deviation management; prototype; and evaluation, together with an introduction, a conclusion and 3 appendices. Demonstrating high utility values and the promise of wide applicability in practice, as well as the potential for an investigation into the transfer of the approach to other domains, the book will be of interest to all those whose work involves workflow management systems.
Book Synopsis Semantics of Belief Change Operators for Intelligent Agents: Iteration, Postulates, and Realizability by : K. Sauerwald
Download or read book Semantics of Belief Change Operators for Intelligent Agents: Iteration, Postulates, and Realizability written by K. Sauerwald and published by IOS Press. This book was released on 2022-11-03 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the core problems in artificial intelligence is the modelling of human reasoning and intelligent behaviour. The representation of knowledge, and reasoning about it, are of crucial importance in achieving this. This book, Semantics of Belief Change Operators for Intelligent Agents: Iteration, Postulates, and Realizability, addresses a number of significant research questions in belief change theory from a semantic point of view; in particular, the connection between different types of belief changes and plausibility relations over possible worlds is investigated. This connection is characterized for revision over general classical logics, showing which relations are capturing AGM revision. In addition, those classical logics for which the correspondence between AGM revision and total preorders holds are precisely characterized. AGM revision in the Darwiche-Pearl framework for belief change over arbitrary sets of epistemic states is considered, demonstrating, especially, that for some sets of epistemic states, no AGM revision operator exists. A characterization of those sets of epistemic states for which AGM revision operators exist is presented. The expressive class of dynamic limited revision operators is introduced to provide revision operators for more sets of epistemic states. Specifications for the acceptance behaviour of various belief-change operators are examined, and those realizable by dynamic-limited revision operators are described. The iteration of AGM contraction in the Darwiche-Pearl framework is explored in detail, several known and novel iteration postulates for contraction are identified, and the relationships among these various postulates are determined. With a convincing presentation of ideas, the book refines and advances existing proposals of belief change, develops novel concepts and approaches, rigorously defines the concepts introduced, and formally proves all technical claims, propositions and theorems, significantly advancing the state-of-the-art in this field.
Book Synopsis Shallow Discourse Parsing for German by : P. Bourgonje
Download or read book Shallow Discourse Parsing for German written by P. Bourgonje and published by IOS Press. This book was released on 2021-07-13 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: The last few decades have seen impressive improvements in several areas of Natural Language Processing. Nevertheless, getting a computer to make sense of the discourse of utterances in a text remains challenging. Several different theories which aim to describe and analyze the coherent structure of a well-written text exist, but with varying degrees of applicability and feasibility for practical use. This book is about shallow discourse parsing, following the paradigm of the Penn Discourse TreeBank, a corpus containing over 1 million words annotated for discourse relations. When it comes to discourse processing, any language other than English must be considered a low-resource language. This book relates to discourse parsing for German. The limited availability of annotated data for German means that the potential of modern, deep-learning-based methods relying on such data is also limited. This book explores to what extent machine-learning and more recent deep-learning-based methods can be combined with traditional, linguistic feature engineering to improve performance for the discourse parsing task. The end-to-end shallow discourse parser for German developed for the purpose of this book is open-source and available online. Work has also been carried out on several connective lexicons in different languages. Strategies are discussed for creating or further developing such lexicons for a given language, as are suggestions on how to further increase their usefulness for shallow discourse parsing. The book will be of interest to all whose work involves Natural Language Processing, particularly in languages other than English.
Book Synopsis From Narratology to Computational Story Composition and Back by : L. Berov
Download or read book From Narratology to Computational Story Composition and Back written by L. Berov and published by IOS Press. This book was released on 2023-03-10 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although both deal with narratives, the two disciplines of Narrative Theory (NT) and Computational Story Composition (CSC) rarely exchange insights and ideas or engage in collaborative research. The former has its roots in the humanities, and attempts to analyze literary texts to derive an understanding of the concept of narrative. The latter is in the domain of Artificial Intelligence, and investigates the autonomous composition of fictional narratives in a way that could be deemed creative. The two disciplines employ different research methodologies at contradistinct levels of abstraction, making simultaneous research difficult, while a close exchange between the two disciplines would undoubtedly be desirable, not least because of the complementary approach to their object of study. This book, From Narratology to Computational Story Composition and Back, describes an exploratory study in generative modeling, a research methodology proposed to address the methodological differences between the two disciplines and allow for simultaneous NT and CSC research. It demonstrates how implementing narratological theories as computational, generative models can lead to insights for NT, and how grounding computational representations of narrative in NT can help CSC systems to take over creative responsibilities. It is the interplay of these two strands that underscores the feasibility and utility of generative modeling. The book is divided into 6 chapters: an introduction, followed by chapters on plot, fictional characters, plot quality estimation, and computational creativity, wrapped up by a conclusion. The book will be of interest to all those working in the fields of narrative theory and computational creativity.
Book Synopsis Representation Learning for Natural Language Processing by : Zhiyuan Liu
Download or read book Representation Learning for Natural Language Processing written by Zhiyuan Liu and published by Springer Nature. This book was released on 2020-07-03 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.
Book Synopsis Neural Representations of Natural Language by : Lyndon White
Download or read book Neural Representations of Natural Language written by Lyndon White and published by Springer. This book was released on 2018-08-29 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers an introduction to modern natural language processing using machine learning, focusing on how neural networks create a machine interpretable representation of the meaning of natural language. Language is crucially linked to ideas – as Webster’s 1923 “English Composition and Literature” puts it: “A sentence is a group of words expressing a complete thought”. Thus the representation of sentences and the words that make them up is vital in advancing artificial intelligence and other “smart” systems currently being developed. Providing an overview of the research in the area, from Bengio et al.’s seminal work on a “Neural Probabilistic Language Model” in 2003, to the latest techniques, this book enables readers to gain an understanding of how the techniques are related and what is best for their purposes. As well as a introduction to neural networks in general and recurrent neural networks in particular, this book details the methods used for representing words, senses of words, and larger structures such as sentences or documents. The book highlights practical implementations and discusses many aspects that are often overlooked or misunderstood. The book includes thorough instruction on challenging areas such as hierarchical softmax and negative sampling, to ensure the reader fully and easily understands the details of how the algorithms function. Combining practical aspects with a more traditional review of the literature, it is directly applicable to a broad readership. It is an invaluable introduction for early graduate students working in natural language processing; a trustworthy guide for industry developers wishing to make use of recent innovations; and a sturdy bridge for researchers already familiar with linguistics or machine learning wishing to understand the other.
Book Synopsis Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing by : Stefan Wermter
Download or read book Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing written by Stefan Wermter and published by Springer Science & Business Media. This book was released on 1996-03-15 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is based on the workshop on New Approaches to Learning for Natural Language Processing, held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI'95, in Montreal, Canada in August 1995. Most of the 32 papers included in the book are revised selected workshop presentations; some papers were individually solicited from members of the workshop program committee to give the book an overall completeness. Also included, and written with the novice reader in mind, is a comprehensive introductory survey by the volume editors. The volume presents the state of the art in the most promising current approaches to learning for NLP and is thus compulsory reading for researchers in the field or for anyone applying the new techniques to challenging real-world NLP problems.
Book Synopsis Data-Driven Methods for Adaptive Spoken Dialogue Systems by : Oliver Lemon
Download or read book Data-Driven Methods for Adaptive Spoken Dialogue Systems written by Oliver Lemon and published by Springer Science & Business Media. This book was released on 2012-10-21 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data driven methods have long been used in Automatic Speech Recognition (ASR) and Text-To-Speech (TTS) synthesis and have more recently been introduced for dialogue management, spoken language understanding, and Natural Language Generation. Machine learning is now present “end-to-end” in Spoken Dialogue Systems (SDS). However, these techniques require data collection and annotation campaigns, which can be time-consuming and expensive, as well as dataset expansion by simulation. In this book, we provide an overview of the current state of the field and of recent advances, with a specific focus on adaptivity.
Book Synopsis Deep Learning in Natural Language Processing by : Li Deng
Download or read book Deep Learning in Natural Language Processing written by Li Deng and published by Springer. This book was released on 2018-05-23 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as a benchmark for the advances in one of the most important tasks in artificial intelligence. This book reviews the state of the art of deep learning research and its successful applications to major NLP tasks, including speech recognition and understanding, dialogue systems, lexical analysis, parsing, knowledge graphs, machine translation, question answering, sentiment analysis, social computing, and natural language generation from images. Outlining and analyzing various research frontiers of NLP in the deep learning era, it features self-contained, comprehensive chapters written by leading researchers in the field. A glossary of technical terms and commonly used acronyms in the intersection of deep learning and NLP is also provided. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers and industrial researchers, as well as anyone interested in deep learning and natural language processing.
Book Synopsis Recognizing Textual Entailment by : Ido Dagan
Download or read book Recognizing Textual Entailment written by Ido Dagan and published by Springer Nature. This book was released on 2022-06-01 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last few years, a number of NLP researchers have developed and participated in the task of Recognizing Textual Entailment (RTE). This task encapsulates Natural Language Understanding capabilities within a very simple interface: recognizing when the meaning of a text snippet is contained in the meaning of a second piece of text. This simple abstraction of an exceedingly complex problem has broad appeal partly because it can be conceived also as a component in other NLP applications, from Machine Translation to Semantic Search to Information Extraction. It also avoids commitment to any specific meaning representation and reasoning framework, broadening its appeal within the research community. This level of abstraction also facilitates evaluation, a crucial component of any technological advancement program. This book explains the RTE task formulation adopted by the NLP research community, and gives a clear overview of research in this area. It draws out commonalities in this research, detailing the intuitions behind dominant approaches and their theoretical underpinnings. This book has been written with a wide audience in mind, but is intended to inform all readers about the state of the art in this fascinating field, to give a clear understanding of the principles underlying RTE research to date, and to highlight the short- and long-term research goals that will advance this technology.
Book Synopsis Natural Language Processing and Chinese Computing by : Juanzi Li
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 610 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.
