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This book presents a unified formal approach to various contemporary linguistic formalisms such as Government & Binding, Minimalism or Tree Adjoining Grammar. Through a careful introduction of mathematical techniques from logic, automata theory and universal algebra, the book aims at graduate students and researchers who want to learn more about tightly constrained logical approaches to natural language syntax. Therefore it features a complete and well illustrated introduction to the connection between declarative approaches formalized in monadic second-order logic (MSO) and generative ones formalized in various forms of automata as well as of tree grammars. Since MSO logic (on trees) yields only context-free languages, and at least the last two of the formalisms mentioned above clearly belong to the class of mildly context-sensitive formalisms, it becomes necessary to deal with the problem of the descriptive complexity of the formalisms involved in another way. The proposed genuinely new two-step approach overcomes this limitation of MSO logic while still retaining the desired tightly controlled formal properties.
This book presents a unified formal approach to various contemporary linguistic formalisms such as Government & Binding, Minimalism or Tree Adjoining Grammar. Through a careful introduction of mathematical techniques from logic, automata theory and universal algebra, the book aims at graduate students and researchers who want to learn more about tightly constrained logical approaches to natural language syntax. Therefore it features a complete and well illustrated introduction to the connection between declarative approaches formalized in monadic second-order logic (MSO) and generative ones formalized in various forms of automata as well as of tree grammars. Since MSO logic (on trees) yields only context-free languages, and at least the last two of the formalisms mentioned above clearly belong to the class of mildly context-sensitive formalisms, it becomes necessary to deal with the problem of the descriptive complexity of the formalisms involved in another way. The proposed genuinely new two-step approach overcomes this limitation of MSO logic while still retaining the desired tightly controlled formal properties.
These proceedings contain the final versions of the papers presented at the 7th International Workshop on Finite-State Methods and Natural Language Processing (FSMNLP), held in Ispra, Italy, on September 11–12, 2008. The aim of the FSMNLP workshops is to bring together members of the research and industrial community working on finite-state based models in language technology, computational linguistics, web mining, linguistics and cognitive science on one hand, and on related theory and methods in fields such as computer science and mathematics on the other. Thus, the workshop series is a forum for researchers and practitioners working on applications as well as theoretical and implementation aspects. The special theme of FSMNLP 2008 was high performance finite-state devices in large-scale natural language text processing systems and applications. The papers in this publication cover a range of interesting NLP applications, including machine learning and translation, logic, computational phonology, morphology and semantics, data mining, information extraction and disambiguation, as well as programming, optimization and compression of finite-state networks. The applied methods include weighted algorithms, kernels and tree automata. In addition, relevant aspects of software engineering, standardization and European funding programmes are discussed.
This book constitutes the refereed proceedings of the Third International Conference on Language and Automata Theory and Applications, LATA 2009, held in Tarragona, Spain, in April 2009. The 58 revised full papers presented together with 3 invited lectures and two tutorials were carefully reviewed and selected from 121 submissions. The papers address all the various issues related to automata theory and formal languages.
This book constitutes the refereed proceedings of the 17th and 18th International Conference on Formal Grammar 2012 and 2013, collocated with the European Summer School in Logic, Language and Information in August 2012/2013. The 18 revised full papers were carefully reviewed and selected from a total of 27 submissions. The focus of papers are as follows: formal and computational phonology, morphology, syntax, semantics and pragmatics; model-theoretic and proof-theoretic methods in linguistics; logical aspects of linguistic structure; constraint-based and resource-sensitive approaches to grammar; learnability of formal grammar; integration of stochastic and symbolic models of grammar; foundational, methodological and architectural issues in grammar and linguistics, and mathematical foundations of statistical approaches to linguistic analysis.
"The workshop that originated this book was entitled "Understanding language : forty years down the garden path". It took place in July 2010." --Acknowledgements p. [xii].
This book provides a thorough introduction to the subfield of theoretical computer science known as grammatical inference from a computational linguistic perspective. Grammatical inference provides principled methods for developing computationally sound algorithms that learn structure from strings of symbols. The relationship to computational linguistics is natural because many research problems in computational linguistics are learning problems on words, phrases, and sentences: What algorithm can take as input some finite amount of data (for instance a corpus, annotated or otherwise) and output a system that behaves "correctly" on specific tasks? Throughout the text, the key concepts of grammatical inference are interleaved with illustrative examples drawn from problems in computational linguistics. Special attention is paid to the notion of "learning bias." In the context of computational linguistics, such bias can be thought to reflect common (ideally universal) properties of natural languages. This bias can be incorporated either by identifying a learnable class of languages which contains the language to be learned or by using particular strategies for optimizing parameter values. Examples are drawn largely from two linguistic domains (phonology and syntax) which span major regions of the Chomsky Hierarchy (from regular to context-sensitive classes). The conclusion summarizes the major lessons and open questions that grammatical inference brings to computational linguistics. Table of Contents: List of Figures / List of Tables / Preface / Studying Learning / Formal Learning / Learning Regular Languages / Learning Non-Regular Languages / Lessons Learned and Open Problems / Bibliography / Author Biographies
This volume brings together philosophers and physicists to explore the parallels between Quantum Bayesianism, or QBism, and the phenomenological tradition. It is the first book exclusively devoted to phenomenology and quantum mechanics. By emphasizing the role of the subject’s experiences and expectations, and by explicitly rejecting the idea that the notion of physical reality could ever be reduced to a purely third-personal perspective, QBism exhibits several interesting parallels with phenomenology. The central message of QBism is that quantum probabilities must be interpreted as the experiencing agent’s personal Bayesian degrees of belief—degrees of belief for the consequences of their actions on a quantum system. The chapters in this volume elaborate whether and specify how phenomenology could serve as the philosophical foundation of QBism. This objective is pursued from the perspective of QBists engaging with phenomenology as well as the perspective of phenomenologists engaging with QBism. These approaches enable us to realize a better understanding of quantum mechanics and the world we live in, achieve a better understanding of QBsim, and introduce the phenomenological foundations of quantum mechanics. Phenomenology and QBism is an essential resource for researchers and graduate students working in philosophy of physics, philosophy of science, quantum mechanics, and phenomenology.