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We present and analyze the star clustering algorithm. We discuss
an implementation of this algorithm that supports browsing and
document retrieval through information organization. We define three
parameters for evaluating a clustering algorithm to measure the topic
separation and topic aggregation achieved by the algorithm. In the
absence of benchmarks, we present a method for randomly generating
clustering data. Data from our user study shows evidence that the star
algorithm is effective for organizing information.
Submitted to the 1998 SIGIR Conference.
Bibliographic citation for this report: [plain text] [BIB] [BibTeX] [Refer]
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J. Aslam, K. Pelekhov, and Daniela Rus, "Generating, Visualizing and Evaluating High Quality Clusters for Information Organization." Dartmouth Computer Science Technical Report PCS-TR97-319, August 1997.
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