DocumentCode :
1739861
Title :
Neural network: an exploration in document retrieval system
Author :
Chandren, Ravie
Author_Institution :
Jabatan Sains Komputer, Univ. Kebangsaan Malaysia, Selangor, Malaysia
Volume :
1
fYear :
2000
fDate :
2000
Firstpage :
156
Abstract :
As more and more information is stored electronically, the demand for intelligent methods becomes increasingly urgent. The basic belief underlying this research is that a truly helpful document retrieval system must “understand” what the user is looking for. A neural network has information processing structure attributes for adaptation to fulfil the needs within an information environment. These attributes are suitable to be used in a document retrieval system in order to build a faster, efficient and user-friendly system. This paper presents experimental research on the effectiveness of a neural network model in document retrieval. The main purpose of this research is to demonstrate the feasibility of the proposed approach. The backpropagation neural network learning method is used to build up and employ application domain knowledge for the document retrieval system. The knowledge is acquired from examples of queries and relevant documents. Then, another collection of queries is used to test the effectiveness of the system
Keywords :
backpropagation; document handling; information retrieval; neural nets; application domain knowledge; backpropagation; document retrieval system; experimental research; information processing; intelligent methods; learning; neural network; queries; user-friendly system; Backpropagation; Costs; Frequency estimation; Information processing; Information retrieval; Intelligent networks; Knowledge based systems; Learning systems; Neural networks; System testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
TENCON 2000. Proceedings
Conference_Location :
Kuala Lumpur
Print_ISBN :
0-7803-6355-8
Type :
conf
DOI :
10.1109/TENCON.2000.893561
Filename :
893561
Link To Document :
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