DocumentCode
350863
Title
Automatic adaptation method in intelligent image retrieval system
Author
Kim, Yong Hwan ; Rhee, Phill Kyu
Author_Institution
Dept. of Comput. Sci., Inha Univ., Inchon, South Korea
Volume
1
fYear
1999
fDate
1999
Firstpage
439
Abstract
Information overload in modern electronic life is an inevitable problem. It is more difficult for users to find information that they need. For resolving this problem, we present the framework design and implementation issues of an image retrieval system called IIRS with the capability of user adaptation. Even though much research has been performed on the development of efficient image retrieval engines, most of this has focused on the performance of the system, not the friendliness and efficiency of the user interface. The satisfaction of users is at least as important as the functionality and performance in image retrieval systems. An intelligent user interface adaptation method enables IIRS to be more intelligent, natural and efficient. We address the adaptation method that consists of a decision tree and backpropagation neural network. They have been employed for long-term and short-term adaptations respectively. Experimental results show that the automatic adaptation method can improve the performance of the IIRS
Keywords
backpropagation; decision trees; deductive databases; human factors; image retrieval; information needs; neural nets; user interfaces; visual databases; IIRS; automatic adaptation method; backpropagation neural network; decision tree; experimental results; image retrieval engines; information needs; information overload; intelligent image retrieval system; intelligent user interface adaptation; performance; user adaptation; user satisfaction; Computer science; Decision trees; Humans; Image resolution; Image retrieval; Information retrieval; Intelligent systems; Neural networks; Search engines; User interfaces;
fLanguage
English
Publisher
ieee
Conference_Titel
TENCON 99. Proceedings of the IEEE Region 10 Conference
Conference_Location
Cheju Island
Print_ISBN
0-7803-5739-6
Type
conf
DOI
10.1109/TENCON.1999.818445
Filename
818445
Link To Document