Cheops: a compact explorer for complex hierarchies
Proceedings of the 7th conference on Visualization '96
Web document clustering: a feasibility demonstration
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Estimating frequency of change
ACM Transactions on Internet Technology (TOIT)
Research report: Interacting with huge hierarchies: beyond cone trees
INFOVIS '95 Proceedings of the 1995 IEEE Symposium on Information Visualization
CubeSVD: a novel approach to personalized Web search
WWW '05 Proceedings of the 14th international conference on World Wide Web
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Web search engines are one of the most widely used applications on the Internet. Still there are no metric or scales to quantitatively determine the quality of web search. Existing result-display approaches adopted by the search engines are limited to hierarchical listing and clustering of result entries. Such practice of information representation does not tell anything about the quality of search which necessitates the exercise of manual skimming of results entries by the users. In this paper, we are invoking the need of a metric for Quality of Web Search (QoWS), and we are presenting a theoretical framework to measure, quantify and visually represent the quality. QoWS model adds another dimension to search engine personalization.