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Titlebook: Connectionist Natural Language Processing; Readings from Connec Noel Sharkey Book 1992 Springer Science+Business Media Dordrecht 1992 artif

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发表于 2025-3-21 18:07:26 | 显示全部楼层 |阅读模式
书目名称Connectionist Natural Language Processing
副标题Readings from Connec
编辑Noel Sharkey
视频videohttp://file.papertrans.cn/236/235621/235621.mp4
图书封面Titlebook: Connectionist Natural Language Processing; Readings from Connec Noel Sharkey Book 1992 Springer Science+Business Media Dordrecht 1992 artif
描述Connection science is a new information-processing paradigmwhich attempts to imitate the architecture and process of the brain,and brings together researchers from disciplines as diverse ascomputer science, physics, psychology, philosophy, linguistics,biology, engineering, neuroscience and AI. Work in ConnectionistNatural Language Processing (CNLP) is now expanding rapidly, yet muchof the work is still only available in journals, some of them quiteobscure. To make this research more accessible this book bringstogether an important and comprehensive set of articles from thejournal .CONNECTION SCIENCE. which represent the state of the artin Connectionist natural language processing; from speech recognitionto discourse comprehension. While it is quintessentiallyConnectionist, it also deals with hybrid systems, and will be ofinterest to both theoreticians as well as computer modellers. .Range of topics covered:.. Connectionism and Cognitive Linguistics .. Motion, Chomsky‘s Government-binding Theory .. Syntactic Transformations on Distributed Representations .. Syntactic Neural Networks .. A Hybrid Symbolic/Connectionist Model for Understanding ofNouns .. Connectionism and Determinism i
出版日期Book 1992
关键词artificial intelligence; cognition; grammar; knowledge; language; learning; linguistics; natural language; n
版次1
doihttps://doi.org/10.1007/978-94-011-2624-3
isbn_softcover978-94-010-5160-6
isbn_ebook978-94-011-2624-3
copyrightSpringer Science+Business Media Dordrecht 1992
The information of publication is updating

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发表于 2025-3-21 20:21:32 | 显示全部楼层
,A Connectionist Model of Motion and Government on Chomsky’s Government-binding Theory,of connectionist units using only two architectures: a two-dimensional map, used to model tree structures, and a one-dimensional row used to model constituent feature assignment. GB theory is a constraint-based theory of syntax. The constraints of GB are modeled by the maps, the rows and the connect
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Syntactic Transformations on Distributed Representations,ty of such models have been proposed. These models typically use distributed representations that arise from the functional composition of constituent parts. Functional composition and decomposition alone, however, yield only an implementation of classical symbolic theories. This paper explores the
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Syntactic Neural Networks,s seen as a process of grammatical inference and recognition as a process of parsing. Naturally, the possible realizations of this theme are diverse; in this paper we present some initial explorations of the case where the pattern grammar is context-free, inferred (from examples) by a separate proce
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Incremental Syntactic Tree Formation in Human Sentence Processing: a Cognitive Architecture Based oically inspired but not based on neural nets. Instead it relies on biosynthesis as a basic metaphor. We use simulated annealing as an optimization technique which searches for the best configuration of isolated syntactic segments or subtrees in the final parse tree. The gradually decaying activation
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A Hybrid Symbolic/Connectionist Model for Noun Phrase Understanding,ee levels: (1) a distributed connectionist level, (2) a localist connectionist level, and (3) a symbolic level. While most current systems in natural language processing use techniques from only one of these three levels, our model takes advantage of the virtues of all three processing paradigms. Th
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Connectionism and Determinism in a Syntactic Parser,a critical role. Writing systems, for example, owe their existence to the symbolic nature of language. It is also subsymbolic because of the nature of speech, the fuzziness of concepts, and the high degree of parallelism that is difficult to explain as a purely symbolic phenomenon. Building a proces
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Script Recognition with Hierarchical Feature Maps, and role bindings. The recognition taxonomy, i.e. the breakdown of each script into the tracks and roles, is extracted automatically and independently for each script from examples of script instantiations in an unsupervised self-organizing process. The process resembles human learning in that the
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