Interactive Cluster Visualization for Information Retrieval (1997) [25 citations — 8 self]
http://www.ict.usc.edu/~leuski/publications/papers
http://ciir.cs.umass.edu/pubfiles/ir-152.pdf
http://cobar.cs.umass.edu/pubfiles/ir-116.ps.gz
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author = {James Allan and Anton V. Leouski and Russell C. Swan},
title = {Interactive Cluster Visualization for Information Retrieval},
institution = {In Proceedings of ECDL'98},
year = {1997}
}
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Abstract:
This study investigates the ability of cluster visualization to help a user rapidly identify relevant documents. It provides added support for the truth of the Cluster Hypothesis on retrieved documents and shows that clustering of relevant documents is readily visible. The study then shows the visual effect of a technique similar to relevance feedback and shows how to enhance that effect to further help the user locate relevant material. A ranked list returned by a text search engine purports to present the documents in the order they are most likely to be relevant: the first document is the best match for the user's query, the second is the next most likely to be helpful, and so on. We are interested in situations where this simple model breaks down---where the user is unable to find enough relevant material in the first or second screens of the list. In particular, we are interested in helping a searcher find all of the relevant material in the top ranked list without forcing him or...
