Relevance Feedback for Content-Based Image Retrieval by Mining User Navigation Patterns
Shinde, Akash G
Gulhane, Suraj M
- Publisher: Journal of Engineering Computers & Applied Sciences
Journal of Engineering Computers & Applied Sciences
Computer Sciences | Ccontent based image retrieval(CBIR), Query Point Movement(QPM),Query-Expansion(QEX),Query Reweighting (QR),Navigation-Pattern-based Relevance Feedback(NPRF)
This paper presents a novel method, Navigation-Pattern-based Relevance Feedback (NPRF), to achieve the highefficiency and effectiveness of CBIR in coping with the large-scale image data. In terms of efficiency, the iterations of feedback are reduced substantially by using the navigation patterns discovered from the user query log. In terms of effectiveness, our proposed search algorithm NPRF Search makes use of the discovered navigation patterns and three kinds of query refinement strategies, Query Point Movement (QPM), Query Reweighting (QR), and Query Expansion (QEX), to converge the search space toward the users intention effectively. By using NPRF method, high quality of image retrieval on RF can be achieved in a small number of feedbacks. The experimental results reveal that NPRF outperforms other existing methods significantly in terms of precision, coverage, and number of feedbacks.