Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
9651727 | International Journal of Approximate Reasoning | 2005 | 26 Pages |
Abstract
Experiments with three different data sets from Web pages and medical literature have shown that the proposed unsupervised clustering approach performs significantly better than traditional clustering algorithms, such as k-means, AutoClass and Hierarchical Clustering (HAG). This abstract geometric model seems have captured the latent semantic structure of documents.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Tsau Young Lin, I-Jen Chiang,