IGroup: a web image search engine with semantic clustering of search results

Authors:
Feng Jing;Changhu Wang;Yuhuan Yao;Kefeng Deng;Lei Zhang;Wei-Ying Ma
Affiliations:
Microsoft Research Asia, Beijing, China;University of, Science and Technology of China, Hefei, China;Tsinghua University, Beijing, China;Microsoft Research Asia, Beijing, China;Microsoft Research Asia, Beijing, China;Microsoft Research Asia, Beijing, China
Venue:
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Year:
2006

Citing 1
Cited 2

Learning to cluster web search results

Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval

Semantic clustering for region-based image retrieval

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Multiple hypergraph clustering of web images by mining Word2Image correlations

Journal of Computer Science and Technology

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Abstract

In this demo, we present IGroup, a Web image search engine that organizes the search results into semantic clusters. Different from all existing Web image search results clustering algorithms that only cluster the top few images using visual or textual features, IGroup first identifies several query-related semantic clusters based on a key phrases extraction algorithm originally proposed for clustering general Web search results. Then, all the resulting images are separated and assigned to corresponding clusters. To make the best use of the clustering results, a new user interface is proposed. Please go to http://igroup.msra.cn for real experience.