1998
@inproceedings{KLC1998,
vgclass = {refpap},
vgproject = {cbir},
author = {Y. H. Kim and K. E. Lee and K. S. Choi and J. H. Yoo and
P. K. Rhee and Y. C. Park},
title = {Personalized Image Retrieval with User's Preference
Model},
editor = {C.-C. Jay Kuo and Shih-Fu Chang and Sethuraman
Panchanathan},
booktitle = {Multimedia Storage and Archiving Systems III (VV02)},
address = {Boston, Massachusetts, USA},
volume = {3527},
series = {SPIE Proceedings},
pages = {47--55},
month = {November},
year = {1998},
note = {(SPIE Symposium on Voice, Video and Data Communications)},
abstract = {Recently, available information resources in the form of
various media have been increasing with rapid speed. Many retrieval
systems for multimedia information resources have been developed only
focused on their efficiency and performance. Therefore, they cannot
deal with user's preferences and interests well. In this paper, we
present the framework design of a personalized image retrieval system
(PIRS) which can reflect user's preferences and interests
incrementally. The prototype of PIRS consists of two major parts:
user's preference model (UPM) and retrieval module (RM). The UPM plays
a role of refining user's query to meet with user's needs. The RM
retrieves proper images for refined query by computing the similarities
between each image and refined query, and the retrieved images are
ordered by these similarities. In this paper, we mainly discuss about
UPM. The incremental machine learning technologies have been employed
to provide the user adaptable and intelligent capability to the system.
The UPM is implemented by decision tree based on incremental tree
induction (ITI), and adaptive resonance theory (ART) network. User's
feedbacks are returned to the UPM, and they modify internal structure
of the UPM. User's iterative retrieval activities with PIRS cause the
UPM to be revised for user's preferences and interests. Therefore, the
PIRS can be adapted to user's preferences and interests. We have
achieved encouraging results through experiments.},
}