Mechanisms of sentence processing: assigning roles to constituents
Parallel distributed processing: explorations in the microstructure of cognition, vol. 2
Neural Computers
Modular construction of time-delay neural networks for speech recognition
Neural Computation
Recursive distributed representations
Artificial Intelligence - On connectionist symbol processing
Learning and applying contextual constraints in sentence comprehension
Artificial Intelligence - On connectionist symbol processing
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Graded State Machines: The Representation of Temporal Contingencies in Simple Recurrent Networks
Machine Learning - Connectionist approaches to language learning
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Lexical and pragmatic disambiguation and re-interpretation in connectionist networks
International Journal of Man-Machine Studies - Special issue: symbolic problem solving in noisy and novel task environments
Activation diffusion: a connectionist network for robust parsing
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
A hybrid and connectionist architecture for a SCANning understanding
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Subsymbolic natural language processing: an integrated model of scripts, lexicon, and memory
Subsymbolic natural language processing: an integrated model of scripts, lexicon, and memory
Retrieving terms and their variants in a lexicalized unification-based framework
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Selection and information: a class-based approach to lexical relationships
Selection and information: a class-based approach to lexical relationships
A Machine-Oriented Logic Based on the Resolution Principle
Journal of the ACM (JACM)
Lexical semantic techniques for corpus analysis
Computational Linguistics - Special issue on using large corpora: II
Inferring discourse relations in context
ACL '92 Proceedings of the 30th annual meeting on Association for Computational Linguistics
ACM SIGART Bulletin
Sequence Learning - Paradigms, Algorithms, and Applications
Document classification and recurrent neural networks
CASCON '95 Proceedings of the 1995 conference of the Centre for Advanced Studies on Collaborative research
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Time is an essential dimension of human natural language understanding but most of the symbolic models applied to linguistic data do not account for temporal structure. In contrast, the models from the connectionist paradigm have a natural ability to perform dynamic processing.After a presentation of some networks with a concern for time, we describe the model for Coincidence Detection which can be thought of as encoding spatio-temporal regularities of the input data. The architecture of the model is inspired from neurobiological studies of the cerebral cortex. It performs a dynamic interpretation of nominal composition and is analyzed in terms of micro-symbolic co-occurrences. The relevance of the Coincidence Detection machinery in language processing shows the significance of time in computational language understanding.