DocumentCode :
3149836
Title :
Sub-symbolic approaches to information retrieval
Author :
Biron, Paul V. ; Kraft, Donald H.
Author_Institution :
Dept. of Libr. & Inf. Sci., California Univ., Los Angeles, CA, USA
Volume :
4
fYear :
1995
fDate :
22-25 Oct 1995
Firstpage :
3567
Abstract :
As a result of the knowledge representations and inferencing techniques used in traditional approaches to information retrieval, previous work has experienced extreme difficulty with fundamental aspects of the information retrieval problem: namely, the ambiguity and uncertainty involved in the relevance relationship between users information needs and documents which might satisfy those needs. Previously, we reviewed recent work in the use of connectionist models and genetic algorithms for relevance feedback. In this work, the underlying mechanisms of connectionist and genetic models, parallel sub-symbolic computation, are explored in more detail. Three characteristics of sub-symbolic approaches are singled out as particularly appropriate for addressing the problems posed by ambiguity and uncertainty: (1) robustness; (2) constructivity; and (3) adaptivity
Keywords :
genetic algorithms; inference mechanisms; information retrieval; knowledge representation; learning systems; neural nets; symbol manipulation; adaptivity; ambiguity; connectionist models; genetic algorithms; heteroassociative memory; inferencing; information retrieval; knowledge representations; neural networks; parallel sub-symbolic computation; uncertainty; Computational modeling; Computer science; Concurrent computing; Feedback; Genetic algorithms; Information retrieval; Information science; Knowledge representation; Libraries; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 1995. Intelligent Systems for the 21st Century., IEEE International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-2559-1
Type :
conf
DOI :
10.1109/ICSMC.1995.538340
Filename :
538340
Link To Document :
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