Introduction to the theory of neural computation
Introduction to the theory of neural computation
A Model for Adaptive Information Retrieval
Journal of Intelligent Information Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Similarity Analysis of Video Sequences Using an Artificial Neural Network
Applied Intelligence
Integrating Relevance Feedback Techniques for Image Retrieval Using Reinforcement Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recommendation agent impact on consumer online shopping: The Movie Magic case study
Expert Systems with Applications: An International Journal
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Many multimedia content-based retrieval systems allow query formulation with user setting of relative importance of features (e.g., color, texture, shape, etc) to mimic the user's perception of similarity. However, the systems do not modify their similarity matching functions, which are defined during the system development. In this paper, we present a neural network-based learning algorithm for adapting similarity matching function toward the user's query preference based on his/her relevance feedback. The relevance feedback is given as ranking errors (misranks) between the retrieved and desired lists of multimedia objects. The algorithm is demonstrated for facial image retrieval using the NIST Mugshot Identification Database with encouraging results.