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- Patrick Saint-Dizier & Evelyne Viegas (1995). Computational Lexical Semantics. Cambridge University Press.Lexical semantics has become a major research area within computational linguistics, drawing from psycholinguistics, knowledge representation, computer algorithms and architecture. Research programmes whose goal is the definition of large lexicons are asking what the appropriate representation structure is for different facets of lexical information. Among these facets, semantic information is probably the most complex and the least explored.Computational Lexical Semantics is one of the first volumes to provide models for the creation of various kinds of computerised lexicons for the automatic treatment of natural language, with applications to machine translation, automatic indexing, and database front-ends, knowledge extraction, among other things. It focuses on semantic issues, as seen by linguists, psychologists, and computer scientists. Besides describing academic research, it also covers ongoing industrial projects.
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I examine one of the conceptual cornerstones of the field known as computational neuroscience, especially as articulated in Churchland et al. (1990), an article that is arguably the locus classicus of this term and its meaning. The authors of that article try, but I claim ultimately fail, to mark off the enterprise of computational neuroscience as an interdisciplinary approach to understanding the cognitive, information-processing functions of the brain. The failure is a result of the fact that the authors provide no principled means to distinguish the study of neural systems as genuinely computational/information-processing from the study of any complex causal process. I then argue for two things. First, that in order to appropriately mark off computational neuroscience, one must be able to assign a semantics to the states over which an attempt to provide a computational explanation is made. Second, I show that neither of the two most popular ways of trying to effect such content assignation -- informational semantics and 'biosemantics' -- can make the required distinction, at least not in a way that a computational neuroscientist should be happy about. The moral of the story as I take it is not a negative one to the effect that computational neuroscience is in principle incapable of doing what it wants to do. Rather, it is to point out some work that remains to be done.
1. Formal semantics in linguistics -- 2. Generalized quantifier theory -- 3. The interface between syntax and semantics -- 4. Anaphora, discourse, and modality -- 5. Focus, presupposition, and negation -- 6. Tense -- 7. Questions -- 8. Plurals -- 9. Computational semantics -- 10. Lexical semantics -- 11. Semantics and related domains.
How can computers distinguish the coherent from the unintelligible, recognize new information in a sentence, or draw inferences from a natural language passage? Computational semantics is an exciting new field that seeks answers to these questions, and this volume is the first textbook wholly devoted to this growing subdiscipline. The book explains the underlying theoretical issues and fundamental techniques for computing semantic representations for fragments of natural language. This volume will be an essential text for computer scientists, linguists, and anyone interested in the development of computational semantics.
Recently, there has been a surge of interest in the lexicon. The demand for a fuller and more adequate understanding of lexical meaning required by developments in computational linguistics, artificial intelligence, and cognitive science has stimulated a refocused interest in linguistics, psychology, and philosophy. Different disciplines have studied lexical structure from their own vantage points, and because scholars have only intermittently communicated across disciplines, there has been little recognition that there is a common subject matter. The conference on which this volume is based brought together interested thinkers across the disciplines of linguistics, philosophy, psychology, and computer science to exchange ideas, discuss a range of questions and approaches to the topic, consider alternative research strategies and methodologies, and formulate interdisciplinary hypotheses concerning lexical organization. The essay subjects discussed include: * alternative and complementary conceptions of the structure of the lexicon, * the nature of semantic relations and of polysemy, * the relation between meanings, concepts, and lexical organization, * critiques of truth-semantics and referential theories of meaning, * computational accounts of lexical information and structure, and * the advantages of thinking of the lexicon as ordered.
This book provides a systematic study of three foundational issues in the semantics of natural language that have been relatively neglected in the past few decades. focuses on the formal characterization of intensions, the nature of an adequate type system for natural language semantics, and the formal power of the semantic representation language proposes a theory that offers a promising framework for developing a computational semantic system sufficiently expressive to capture the properties of natural language meaning while remaining computationally tractable written by two leading researchers and of interest to students and researchers in formal semantics, computational linguistics, logic, artificial intelligence, and the philosophy of language.
Lexical ambiguity presents one of the most intractable problems for language processing studies and, not surprisingly, it is at the core of research in lexical semantics. Originally published as two special issues of the Journal of Semantics, this collection focuses on the problem of polysemy, from the point of view of practitioners of computational linguistics.
A primary problem in the area of natural language processing has been semantic analysis. This book looks at the semantics of natural languages in context. It presents an approach to the computational processing of English text that combines current theories of knowledge representation and reasoning in Artificial Intelligence with the latest linguistic views of lexical semantics. The book will interest postgraduates and researchers in computational linguistics as well as industrial research groups specializing in natural language processing.
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