| Literature DB >> 17218746 |
Emilio Di Giacomo1, Walter Didimo, Luca Grilli, Giuseppe Liotta.
Abstract
One of the most challenging issues in mining information from the World Wide Web is the design of systems that present the data to the end user by clustering them into meaningful semantic categories. We show that the analysis of the results of a clustering engine can significantly take advantage of enhanced graph drawing and visualization techniques. We propose a graph-based user interface for Web clustering engines that makes it possible for the user to explore and visualize the different semantic categories and their relationships at the desired level of detail.Mesh:
Year: 2007 PMID: 17218746 DOI: 10.1109/TVCG.2007.40
Source DB: PubMed Journal: IEEE Trans Vis Comput Graph ISSN: 1077-2626 Impact factor: 4.579