Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Fast and effective text mining using linear-time document clustering
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Agglomerative clustering of a search engine query log
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Clustering user queries of a search engine
Proceedings of the 10th international conference on World Wide Web
On Image Classification: City vs. Landscape
CBAIVL '98 Proceedings of the IEEE Workshop on Content - Based Access of Image and Video Libraries
Towards Automatic Generation of Query Taxonomy: A Hierarchical Query Clustering Approach
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Labeling Nodes of Automatically Generated Taxonomy for Multi-type Relational Datasets
DaWaK '08 Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery
Exploiting Domain Knowledge by Automated Taxonomy Generation in Recommender Systems
EC-Web 2009 Proceedings of the 10th International Conference on E-Commerce and Web Technologies
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In this paper, we propose an approach to automatically generating a Yahoo!-like topic hierarchy for organizing Web images from users' perspectives. Relatively little effort has been devoted towards providing such a taxonomy simultaneously considering users' image requests for semantic and visual information. Based on the characteristic that a Web-image query may be refined by various attributes, the proposed approach hierarchically groups similar queries from search engine logs into topic classes at different semantic levels. The generated topic hierarchy has the advantages of organizing image data from users' perspectives for browsing, searching, annotation and users' needs analysis.A series of experiments have been conducted on real-world image search engine logs. Experimental results show that the proposed approach is feasible to generate topic hierarchies for Web images. Moreover, the generated hierarchy has been successfully applied to analysis of users' search interests, which have more focuses on some specific domains when compared with document requests.