DocumentCode :
3636959
Title :
An associative information retrieval algorithm for a Kanerva-like memory model
Author :
Slobodan Ribarić;Darijan Marčetić
Author_Institution :
Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, 10000, Croatia
fYear :
2010
Firstpage :
738
Lastpage :
743
Abstract :
This paper presents an associative information retrieval algorithm for a Kanerva-like sparse distributed memory (SDM) model. This memory model is used to implement the associative level of a hierarchical heterogeneous knowledge-base model consisting of multi-levels, starting from an associative level, through to the semantic, rule-based and description-generator level as the top level in the hierarchy. The architecture of knowledge-base was inspired by biological and psychological models. The proposed algorithm retrieves concepts from the associative level based on the similarity between a concept of interest and already stored concepts. The similarity is expressed by a value of the linguistic variable. With this approach it is possible to solve a problem when the inference processes at the semantic level encounter an unknown concept of interest. The algorithm is demonstrated by retrieving concepts that were stored based on the results of psychological experiment.
Keywords :
"Information retrieval","Biological system modeling","Psychology","Fuzzy logic","Inference algorithms","Distributed computing","Brain modeling","Animals","Humans"
Publisher :
ieee
Conference_Titel :
MIPRO, 2010 Proceedings of the 33rd International Convention
Print_ISBN :
978-1-4244-7763-0
Type :
conf
Filename :
5533510
Link To Document :
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