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IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 2
Extracting Distributed Representations of Concepts and Relations from Positive and Negative Propositions
Como, Italy
July 24-July 27
ISBN: 0-7695-0619-4
Alberto Paccanaro, University College London
Geoffrey E. Hinton, University College London
Linear Relational Embedding (LRE) was introduced (Paccanaro and Hinton, 1999) as a means of extracting a distributed representation of concepts from relational data. The original formulation cannot use negative information and cannot properly handle data in which there are multiple correct answers. In this paper, we propose an extended formulation of LRE that solves both these problems. We present results in two simple domains, which show that learning leads to good generalization.
Citation:
Alberto Paccanaro, Geoffrey E. Hinton, "Extracting Distributed Representations of Concepts and Relations from Positive and Negative Propositions," ijcnn, vol. 2, pp.2259, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 2, 2000
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