A quantum information retrieval approach to memory


Autoria(s): Kitto, Kirsty; Bruza, Peter D.; Gabora, Liane
Data(s)

2012

Resumo

As computers approach the physical limits of information storable in memory, new methods will be needed to further improve information storage and retrieval. We propose a quantum inspired vector based approach, which offers a contextually dependent mapping from the subsymbolic to the symbolic representations of information. If implemented computationally, this approach would provide exceptionally high density of information storage, without the traditionally required physical increase in storage capacity. The approach is inspired by the structure of human memory and incorporates elements of Gardenfors’ Conceptual Space approach and Humphreys et al.’s matrix model of memory.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/49675/

Publicador

IEEE

Relação

http://eprints.qut.edu.au/49675/1/PID2287765.pdf

DOI:10.1109/IJCNN.2012.6252492

Kitto, Kirsty, Bruza, Peter D., & Gabora, Liane (2012) A quantum information retrieval approach to memory. In Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN 2012), IEEE, Brisbane Convention Centre , Brisbane, Qld.

http://purl.org/au-research/grants/ARC/DP1094974

Fonte

School of Information Systems; Science & Engineering Faculty

Palavras-Chave #080110 Simulation and Modelling #080704 Information Retrieval and Web Search #170204 Linguistic Processes (incl. Speech Production and Comprehension) #170205 Neurocognitive Patterns and Neural Networks #context #conceptual space #matrix model #memory #cognitive models
Tipo

Conference Paper