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
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