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This book is a collection of papers written by outstanding researchers in the newly emerging field of computational semantics. It is aimed at those linguists, computer scientists, and logicians who want to know more about the algorithmic realization of meaning in natural language and about what is happening in this field of research. It includes a general introduction by the editors.
A contribution to the emerging discipline of computational semantics, which is concerned with computing the meanings of linguistic objects such as sentences, text fragments, and dialogue. Here researchers offer 17 studies for linguists, computer scientists, and logicians interesting in knowing more about the algorithmic realization of meaning in natural language. The topics include dynamic and underspecified interpretation without dynamic or underspecified logic, minimum description length and compositionality, semantically based ellipsis resolution with syntactic presuppositions, dynamic discourse referents for tense and modals, and a disambiguation approach for German compounds with de-verbal head. Annotation copyrighted by Book News, Inc., Portland, OR
This book is a collection of papers by leading researchers in computational semantics. It presents a state-of-the-art overview of recent and current research in computational semantics, including descriptions of new methods for constructing and improving resources for semantic computation, such as WordNet, VerbNet, and semantically annotated corpora. It also presents new statistical methods in semantic computation, such as the application of distributional semantics in the compositional calculation of sentence meanings. Computing the meaning of sentences, texts, and spoken or texted dialogue is the ultimate challenge in natural language processing, and the key to a wide range of exciting applications. The breadth and depth of coverage of this book makes it suitable as a reference and overview of the state of the field for researchers in Computational Linguistics, Semantics, Computer Science, Cognitive Science, and Artificial Intelligence. ​
This book is a collection of papers written by outstanding researchers in the newly emerging field of computational semantics. It is aimed at those linguists, computer scientists, and logicians who want to know more about the algorithmic realization of meaning in natural language and about what is happening in this field of research. It includes a general introduction by the editors.
Cutting-edge historians explore ideas, communities, and technologies around modern computing to explore how computers mediate social relations. Computers have been framed both as a mirror for the human mind and as an irreducible other that humanness is defined against, depending on different historical definitions of "humanness." They can serve both liberation and control because some people's freedom has historically been predicated on controlling others. Historians of computing return again and again to these contradictions, as they often reveal deeper structures. Using twin frameworks of abstraction and embodiment, a reformulation of the old mind-body dichotomy, this anthology examines how social relations are enacted in and through computing. The authors examining "Abstraction" revisit central concepts in computing, including "algorithm," "program," "clone," and "risk." In doing so, they demonstrate how the meanings of these terms reflect power relations and social identities. The section on "Embodiments" focuses on sensory aspects of using computers as well as the ways in which gender, race, and other identities have shaped the opportunities and embodied experiences of computer workers and users. Offering a rich and diverse set of studies in new areas, the book explores such disparate themes as disability, the influence of the punk movement, working mothers as technical innovators, and gaming behind the Iron Curtain. Abstractions and Embodiments reimagines computing history by questioning canonical interpretations, foregrounding new actors and contexts, and highlighting neglected aspects of computing as an embodied experience. It makes the profound case that both technology and the body are culturally shaped and that there can be no clear distinction between social, intellectual, and technical aspects of computing. Contributors: Janet Abbate, Marc Aidinoff, Troy Kaighin Astarte, Ekaterina Babinsteva, André Brock, Maarten Bullynck, Jiahui Chan, Gerardo Con Diaz, Liesbeth De Mol, Stephanie Dick, Kelcey Gibbons, Elyse Graham, Michael J. Halvorson, Mar Hicks, Scott Kushner, Xiaochang Li, Zachary Loeb, Lisa Nakamura, Tiffany Nichols, Laine Nooney, Elizabeth Petrick, Cierra Robson, Hallam Stevens, Jaroslav Švelch
English Words: History and Structure is concerned primarily with the learned vocabulary of English, the words borrowed from the classical languages. It surveys the historical events that define the layers of vocabulary in English, introduces some of the basic principles of linguistic analysis, and is a helpful manual for vocabulary discernment and enrichment. Exercises accompanying each chapter and further readings on recent loans and the legal and medical vocabulary of English will be available online in the near future. * Introduces students to some basic linguistic terms needed for the discussion of phonological and morphological changes accompanying word formation * Designed to lead students to a finer appreciation of their language and greater ability to recognize relationships between words and discriminate between meanings * An informative appendix discusses the history and usefulness of the best known British and American dictionaries * Online readings and exercises to deepen and strengthen knowledge acquired in the classroom
Introduction. Historical Overview. Databases: Office Information Systems Engineering (J. Palazzo, D. Alcoba) Artificial Intelligence, Logic, and Functional Programming: A HyperIcon Interface to a Blackboard System for Planning Research Projects (P. Charlton, C. Burdorf). Algorithms and Data Structures: Classification of Quadratic Algorithms for Multiplying Polynomials of Small Degree Over Finite Fields (A. Averbuch et al.). Object Oriented Systems: A Graphical Interactive Object Oriented Development System (M. Adar et al.). Distributed Systems: Preserving Distributed Data Coherence Us.
Communities of Computing is the first book-length history of the Association for Computing Machinery (ACM), founded in 1947 and with a membership today of 100,000 worldwide. It profiles ACM's notable SIGs, active chapters, and individual members, setting ACM's history into a rich social and political context. The book's 12 core chapters are organized into three thematic sections. "Defining the Discipline" examines the 1960s and 1970s when the field of computer science was taking form at the National Science Foundation, Stanford University, and through ACM's notable efforts in education and curriculum standards. "Broadening the Profession" looks outward into the wider society as ACM engaged with social and political issues - and as members struggled with balancing a focus on scientific issues and awareness of the wider world. Chapters examine the social turbulence surrounding the Vietnam War, debates about the women's movement, efforts for computing and community education, and international issues including professionalization and the Cold War. "Expanding Research Frontiers" profiles three areas of research activity where ACM members and ACM itself shaped notable advances in computing, including computer graphics, computer security, and hypertext. Featuring insightful profiles of notable ACM leaders, such as Edmund Berkeley, George Forsythe, Jean Sammet, Peter Denning, and Kelly Gotlieb, and honest assessments of controversial episodes, the volume deals with compelling and complex issues involving ACM and computing. It is not a narrow organizational history of ACM committees and SIGS, although much information about them is given. All chapters are original works of research. Many chapters draw on archival records of ACM's headquarters, ACM SIGs, and ACM leaders. This volume makes a permanent contribution to documenting the history of ACM and understanding its central role in the history of computing.
A new framework for understanding computing: a coherent set of principles spanning technologies, domains, algorithms, architectures, and designs. Computing is usually viewed as a technology field that advances at the breakneck speed of Moore's Law. If we turn away even for a moment, we might miss a game-changing technological breakthrough or an earthshaking theoretical development. This book takes a different perspective, presenting computing as a science governed by fundamental principles that span all technologies. Computer science is a science of information processes. We need a new language to describe the science, and in this book Peter Denning and Craig Martell offer the great principles framework as just such a language. This is a book about the whole of computing—its algorithms, architectures, and designs. Denning and Martell divide the great principles of computing into six categories: communication, computation, coordination, recollection, evaluation, and design. They begin with an introduction to computing, its history, its many interactions with other fields, its domains of practice, and the structure of the great principles framework. They go on to examine the great principles in different areas: information, machines, programming, computation, memory, parallelism, queueing, and design. Finally, they apply the great principles to networking, the Internet in particular. Great Principles of Computing will be essential reading for professionals in science and engineering fields with a “computational” branch, for practitioners in computing who want overviews of less familiar areas of computer science, and for non-computer science majors who want an accessible entry way to the field.
According to Rosalind Picard, if we want computers to be genuinely intelligent and to interact naturally with us, we must give computers the ability to recognize, understand, even to have and express emotions. The latest scientific findings indicate that emotions play an essential role in decision making, perception, learning, and more—that is, they influence the very mechanisms of rational thinking. Not only too much, but too little emotion can impair decision making. According to Rosalind Picard, if we want computers to be genuinely intelligent and to interact naturally with us, we must give computers the ability to recognize, understand, even to have and express emotions. Part 1 of this book provides the intellectual framework for affective computing. It includes background on human emotions, requirements for emotionally intelligent computers, applications of affective computing, and moral and social questions raised by the technology. Part 2 discusses the design and construction of affective computers. Although this material is more technical than that in Part 1, the author has kept it less technical than typical scientific publications in order to make it accessible to newcomers. Topics in Part 2 include signal-based representations of emotions, human affect recognition as a pattern recognition and learning problem, recent and ongoing efforts to build models of emotion for synthesizing emotions in computers, and the new application area of affective wearable computers.