Title :
Neural network based retrieval issue on prototype database systems
Author :
Ouyang, Yen Chieh ; Jermann, William
Author_Institution :
Dept. of Electr. Eng., Memphis State Univ., TN, USA
Abstract :
A prototype database system using neural network associative memory is proposed. A new measurement of Hamming distance is discussed in order to examine the closeness between the probe vector and the store vector. A reduced interconnection neural network technique is used to construct a tree index database system. A multiple query is used in the model to retrieve a multiple output
Keywords :
content-addressable storage; database management systems; database theory; information retrieval systems; information storage; neural nets; DBMS; Hamming distance; content addressable storage; database theory; information retrieval; information storage; multiple query; neural network associative memory; neural network based retrieval; probe vector; reduced interconnection neural network technique; store vector; tree index database system; Associative memory; CADCAM; Computer aided manufacturing; Database systems; Hamming distance; Information retrieval; Neural networks; Neurons; Probes; Prototypes;
Conference_Titel :
Systems, Man, and Cybernetics, 1991. 'Decision Aiding for Complex Systems, Conference Proceedings., 1991 IEEE International Conference on
Conference_Location :
Charlottesville, VA
Print_ISBN :
0-7803-0233-8
DOI :
10.1109/ICSMC.1991.169899
