Artificial Intelligence - On connectionist symbol processing
An interactive system for finding complementary literatures: a stimulus to scientific discovery
Artificial Intelligence - Special issue on scientific discovery
Using latent semantic indexing for literature based discovery
Journal of the American Society for Information Science
Binary Spatter-Coding of Ordered K-Tuples
ICANN 96 Proceedings of the 1996 International Conference on Artificial Neural Networks
Holographic Reduced Representation: Distributed Representation for Cognitive Structures
Holographic Reduced Representation: Distributed Representation for Cognitive Structures
The Geometry of Information Retrieval
The Geometry of Information Retrieval
Journal of Biomedical Informatics - Special issue: Unified medical language system
Measuring semantic similarity by latent relational analysis
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Journal of Biomedical Informatics
Arguments of nominals in semantic interpretation of biomedical text
BioNLP '10 Proceedings of the 2010 Workshop on Biomedical Natural Language Processing
Discovering discovery patterns with predication-based Semantic Indexing
Journal of Biomedical Informatics
Real, complex, and binary semantic vectors
QI'12 Proceedings of the 6th international conference on Quantum Interaction
Many paths lead to discovery: analogical retrieval of cancer therapies
QI'12 Proceedings of the 6th international conference on Quantum Interaction
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In this paper, we investigate the ability of the Predication-based Semantic Indexing (PSI) approach, which incorporates both symbolic and distributional information, to support inference on the basis of structural similarity. For example, given a pair of related concepts prozac: depression, we attempt to identify concepts that relate to a third concept, such as schizophrenia in the same way. A novel PSI implementation based on Kanerva's Binary Spatter Code is developed, and evaluated on over 100,000 searches across 180,285 unique concepts and multiple typed relations. PSI is shown to retrieve with accuracy concepts on the basis of shared single and paired relations, given either a single strong example pair, or the superposition of a set of weaker examples. Search space size is identical for single and double relations, providing an efficient means to direct search across predicate paths for the purpose of literature-based discovery.