A Hybrid Symbolic/Connectionist Model for Noun Phrase Understanding
作者:
STEFAN WERMTER,
WENDYG. LEHNERT,
期刊:
Connection Science
(Taylor Available online 1989)
卷期:
Volume 1,
issue 3
页码: 255-272
ISSN:0954-0091
年代: 1989
DOI:10.1080/09540098908915641
出版商: Taylor & Francis Group
关键词: Natural language processing;connectionism;hybrid models;parallel distributed processing;relaxation networks;backpropagation;connectionist/symbolic systems
数据来源: Taylor
摘要:
This paper describes a hybrid model which integrates symbolic and connectionist techniques for the analysis of noun phrases. Our model consists of three 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. The distributed connectionist level provides a learned semantic memory model. The localist connectionist level integrates semantic and syntactic constraints. The symbolic level is responsible for restricted syntactic analysis and concept extraction. We conclude that a hybrid model is potentially stronger than models that rely on only one processing paradigm.
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