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.
CITATION STYLE
Aslam, J., Pelekhov, K., & Rus, D. (1998). Generating, visualizing, and evaluating high-quality clusters for information organization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1481, pp. 53–69). Springer Verlag. https://doi.org/10.1007/3-540-49654-8_5
Mendeley helps you to discover research relevant for your work.