Structured connectionist models of semantic networks

In this paper, we review some connectionist realizations of semantic networks. We focus on models that are generally referred to as structured connectionist models. In addition to reviewing three specific models, we discuss the intimate relationship between semantic networks and connectionist models of knowledge representation. We point out the need for massively parallel realizations of semantic networks and show that structured connectionism offers an appropriate computational framework for doing so.

[1]  Geoffrey E. Hinton,et al.  A Distributed Connectionist Production System , 1988, Cogn. Sci..

[2]  Ronald J. Brachman,et al.  "I Lied About the Trees", Or, Defaults and Definitions in Knowledge Representation , 1985, AI Mag..

[3]  David S. Touretzky,et al.  Cancellation in a Parallel Semantic Network , 1981, IJCAI.

[4]  Scott E. Fahlman,et al.  NETL: A System for Representing and Using Real-World Knowledge , 1979, CL.

[5]  Lenhart K. Schubert.  Semantic Nets are in the Eye of the Beholder , 1991, Principles of Semantic Networks.

[6]  Geoffrey E. Hinton,et al.  Mundane Reasoning by Parallel Constraint Satisfaction , 1990 .

[7]  S. H. Weber.  A structured connectionist approach to direct inferences and figurative adjective-noun combinations , 1990 .

[8]  James Alexander Hendler,et al.  integrating Marker Passing and Problem Solving: A Spreading Activation Approach To Improved Choice in Planning , 1987 .

[9]  Garrison W. Cottrell,et al.  A connectionist approach to word sense disambiguation , 1988 .

[10]  L. Shastri,et al.  From simple associations to systematic reasoning: A connectionist representation of rules, variables and dynamic bindings using temporal synchrony , 1993, Behavioral and Brain Sciences.

[11]  Mark Alan Fanty.  Learning in structured connectionist networks , 1988 .

[12]  Eugene Charniak,et al.  Passing Markers: A Theory of Contextual Influence in Language Comprehension* , 1983 .

[13]  H. Levesque.  Logic and the complexity of reasoning , 1988 .

[14]  Michael G. Dyer,et al.  High-level Inferencing in a Connectionist Network , 1989 .

[15]  G. G. Lendaris.  Conceptual graph knowledge systems as problem context for neural networks , 1988, IEEE 1988 International Conference on Neural Networks.

[16]  Jerome A. Feldman,et al.  Connectionist Models and Their Properties , 1982, Cogn. Sci..

[17]  LOKENDRA SHASTRI,et al.  CONNECTIONISM AND THE COMPUTATIONAL EFFECTIVENESS OF REASONING , 1990 .

[18]  Lokendra Shastri,et al.  Default Reasoning in Semantic Networks: A Formalization of Recognition and Inheritance , 1989, Artificial Intelligence.

[19]  John A. Barnden.  Neural-Net Implementation of Complex Symbol-Processing in a Mental Model Approach to Syllogistic Reasoning , 1989, IJCAI.

[20]  Nicholas V. Findler,et al.  Associative Networks- Representation and Use of Knowledge by Computers , 1980, CL.

[21]  Joachim Diederich,et al.  Instruction and High-level Learning in Connectionist Networks , 1989 .