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ICMCS
2000
IEEE
170views Multimedia» more  ICMCS 2000»
15 years 1 months ago
Update Relevant Image Weights for Content-Based Image Retrieval using Support Vector Machines
Relevance feedback [1] has been a powerful tool for interactive Content-Based Image Retrieval (CBIR). During the retrieval process, the user selects the most relevant images and p...
Qi Tian, Pengyu Hong, Thomas S. Huang
ICIP
2000
IEEE
15 years 11 months ago
Incorporate Support Vector Machines to Content-Based Image Retrieval with Relevant Feedback
By using relevance feedback [6], Content-Based Image Retrieval (CBIR) allows the user to retrieve images interactively. The user can select the most relevant images and provide a ...
Pengyu Hong, Qi Tian, Thomas S. Huang
UM
2009
Springer
15 years 4 months ago
How Users Perceive and Appraise Personalized Recommendations
Abstract. Traditional websites have long relied on users revealing their preferences explicitly through direct manipulation interfaces. However recent recommender systems have gone...
Nicolas Jones, Pearl Pu, Li Chen
LWA
2007
14 years 11 months ago
Towards Learning User-Adaptive State Models in a Conversational Recommender System
Typical conversational recommender systems support interactive strategies that are hard-coded in advance and followed rigidly during a recommendation session. In fact, Reinforceme...
Tariq Mahmood, Francesco Ricci
77
Voted
SG
2010
Springer
15 years 2 months ago
Art 101: Learning to Draw through Sketch Recognition
iCanDraw is a drawing tool that can assist novice users to draw. The goal behind the system is to enable the users to perceive objects beyond what they know and improve their spati...
Tracy Hammond, Manoj Prasad, Daniel Dixon