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Subsymbolic Natural Language Processing

1993 Computers
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Release : 1993
Genre : Computers
Kind : eBook
Book Rating : 909/5 ( reviews)

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Book Synopsis Subsymbolic Natural Language Processing by : Risto Miikkulainen

Download or read book Subsymbolic Natural Language Processing written by Risto Miikkulainen. This book was released on 1993. Available in PDF, EPUB and Kindle. Book excerpt: Risto Miikkulainen draws on recent connectionist work in language comprehension tocreate a model that can understand natural language. Using the DISCERN system as an example, hedescribes a general approach to building high-level cognitive models from distributed neuralnetworks and shows how the special properties of such networks are useful in modeling humanperformance. In this approach connectionist networks are not only plausible models of isolatedcognitive phenomena, but also sufficient constituents for complete artificial intelligencesystems.Distributed neural networks have been very successful in modeling isolated cognitivephenomena, but complex high-level behavior has been tractable only with symbolic artificialintelligence techniques. Aiming to bridge this gap, Miikkulainen describes DISCERN, a completenatural language processing system implemented entirely at the subsymbolic level. In DISCERN,distributed neural network models of parsing, generating, reasoning, lexical processing, andepisodic memory are integrated into a single system that learns to read, paraphrase, and answerquestions about stereotypical narratives.Miikkulainen's work, which includes a comprehensive surveyof the connectionist literature related to natural language processing, will prove especiallyvaluable to researchers interested in practical techniques for high-level representation,inferencing, memory modeling, and modular connectionist architectures.Risto Miikkulainen is anAssistant Professor in the Department of Computer Sciences at The University of Texas atAustin.

Beyond Quantity

2023-11-30 Social Science
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Release : 2023-11-30
Genre : Social Science
Kind : eBook
Book Rating : 668/5 ( reviews)

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Book Synopsis Beyond Quantity by : Andreas Sudmann

Download or read book Beyond Quantity written by Andreas Sudmann. This book was released on 2023-11-30. Available in PDF, EPUB and Kindle. Book excerpt: How do artificial neural networks and other forms of artificial intelligence interfere with methods and practices in the sciences? Which interdisciplinary epistemological challenges arise when we think about the use of AI beyond its dependency on big data? Not only the natural sciences, but also the social sciences and the humanities seem to be increasingly affected by current approaches of subsymbolic AI, which master problems of quality (fuzziness, uncertainty) in a hitherto unknown way. But what are the conditions, implications, and effects of these (potential) epistemic transformations and how must research on AI be configured to address them adequately?

Handbook of Natural Language Processing

2000-07-25 Business & Economics
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Release : 2000-07-25
Genre : Business & Economics
Kind : eBook
Book Rating : 004/5 ( reviews)

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Book Synopsis Handbook of Natural Language Processing by : Robert Dale

Download or read book Handbook of Natural Language Processing written by Robert Dale. This book was released on 2000-07-25. Available in PDF, EPUB and Kindle. Book excerpt: This study explores the design and application of natural language text-based processing systems, based on generative linguistics, empirical copus analysis, and artificial neural networks. It emphasizes the practical tools to accommodate the selected system.

Connectionist Natural Language Processing

2012-12-06 Language Arts & Disciplines
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Release : 2012-12-06
Genre : Language Arts & Disciplines
Kind : eBook
Book Rating : 240/5 ( reviews)

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Book Synopsis Connectionist Natural Language Processing by : Noel Sharkey

Download or read book Connectionist Natural Language Processing written by Noel Sharkey. This book was released on 2012-12-06. Available in PDF, EPUB and Kindle. Book excerpt: Connection science is a new information-processing paradigm which attempts to imitate the architecture and process of the brain, and brings together researchers from disciplines as diverse as computer science, physics, psychology, philosophy, linguistics, biology, engineering, neuroscience and AI. Work in Connectionist Natural Language Processing (CNLP) is now expanding rapidly, yet much of the work is still only available in journals, some of them quite obscure. To make this research more accessible this book brings together an important and comprehensive set of articles from the journal CONNECTION SCIENCE which represent the state of the art in Connectionist natural language processing; from speech recognition to discourse comprehension. While it is quintessentially Connectionist, it also deals with hybrid systems, and will be of interest 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 of Nouns Connectionism and Determinism in a Syntactic Parser Context Free Grammar Recognition Script Recognition with Hierarchical Feature Maps Attention Mechanisms in Language Script-Based Story Processing A Connectionist Account of Similarity in Vowel Harmony Learning Distributed Representations Connectionist Language Users Representation and Recognition of Temporal Patterns A Hybrid Model of Script Generation Networks that Learn about Phonological Features Pronunciation in Text-to-Speech Systems

A Practical Guide to Hybrid Natural Language Processing

2020-06-16 Computers
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Release : 2020-06-16
Genre : Computers
Kind : eBook
Book Rating : 304/5 ( reviews)

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Book Synopsis A Practical Guide to Hybrid Natural Language Processing by : Jose Manuel Gomez-Perez

Download or read book A Practical Guide to Hybrid Natural Language Processing written by Jose Manuel Gomez-Perez. This book was released on 2020-06-16. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with a practical guide to the principles of hybrid approaches to natural language processing (NLP) involving a combination of neural methods and knowledge graphs. To this end, it first introduces the main building blocks and then describes how they can be integrated to support the effective implementation of real-world NLP applications. To illustrate the ideas described, the book also includes a comprehensive set of experiments and exercises involving different algorithms over a selection of domains and corpora in various NLP tasks. Throughout, the authors show how to leverage complementary representations stemming from the analysis of unstructured text corpora as well as the entities and relations described explicitly in a knowledge graph, how to integrate such representations, and how to use the resulting features to effectively solve NLP tasks in a range of domains. In addition, the book offers access to executable code with examples, exercises and real-world applications in key domains, like disinformation analysis and machine reading comprehension of scientific literature. All the examples and exercises proposed in the book are available as executable Jupyter notebooks in a GitHub repository. They are all ready to be run on Google Colaboratory or, if preferred, in a local environment. A valuable resource for anyone interested in the interplay between neural and knowledge-based approaches to NLP, this book is a useful guide for readers with a background in structured knowledge representations as well as those whose main approach to AI is fundamentally based on logic. Further, it will appeal to those whose main background is in the areas of machine and deep learning who are looking for ways to leverage structured knowledge bases to optimize results along the NLP downstream.

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