Recent trends in hierarchic document clustering: a critical review
Information Processing and Management: an International Journal
Information retrieval: data structures and algorithms
Information retrieval: data structures and algorithms
International Journal of Computer Vision
Efficient and effective querying by image content
Journal of Intelligent Information Systems - Special issue: advances in visual information management systems
The cluster hypothesis revisited
SIGIR '85 Proceedings of the 8th annual international ACM SIGIR conference on Research and development in information retrieval
NeTra: a toolbox for navigating large image databases
Multimedia Systems - Special issue on video content based retrieval
Unifying textual and visual cues for content-based image retrieval on the World Wide Web
Computer Vision and Image Understanding - Special issue on content-based access for image and video libraries
SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries
IEEE Transactions on Pattern Analysis and Machine Intelligence
The effectiveness of query-specific hierarchic clustering in information retrieval
Information Processing and Management: an International Journal
Blobworld: Image Segmentation Using Expectation-Maximization and Its Application to Image Querying
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Ranking Algorithm Using Dynamic Clustering for Content-Based Image Retrieval
CIVR '02 Proceedings of the International Conference on Image and Video Retrieval
WebSeer: An Image Search Engine for the World Wide Web
WebSeer: An Image Search Engine for the World Wide Web
Canonical image selection from the web
Proceedings of the 6th ACM international conference on Image and video retrieval
Pagerank for product image search
Proceedings of the 17th international conference on World Wide Web
Learning social tag relevance by neighbor voting
IEEE Transactions on Multimedia
The state of the art in image and video retrieval
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
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In this paper, we address a ranking problem in web image retrieval. Due to the growing availability of web images, comprehensive retrieval of web images has been expected. Conventional systems for web image retrieval are based on keyword- based retrieval. However, we often find undesirable retrieval results from the keyword based web image retrieval system since the system uses the limited and inaccurate text information of web images ; a typical system uses text information such as surrounding texts and/or image filenames, etc. To alleviate this situation, we propose a new ranking approach which is the integration of results of text and image content via analyzing the retrieved results. We define four ranking methods based on the image contents analysis of the retrieved images; (1) majority-first method, (2) centroid-of-all method, (3) centroid-of-top K method, and (4) centroid-of-largest-cluster method. We evaluate the retrieval performance of our methods and conventional one using precision and recall graphs. The experimental results show that the proposed methods are more effective than conventional keyword-based retrieval methods.