Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Web document clustering: a feasibility demonstration
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Grouper: a dynamic clustering interface to Web search results
WWW '99 Proceedings of the eighth international conference on World Wide Web
Computing Orthogonal Drawings with the Minimum Number of Bends
IEEE Transactions on Computers
A clustering algorithm based on graph connectivity
Information Processing Letters
A topology-driven approach to the design of web meta-search clustering engines
SOFSEM'05 Proceedings of the 31st international conference on Theory and Practice of Computer Science
Graph Visualization Techniques for Web Clustering Engines
IEEE Transactions on Visualization and Computer Graphics
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One of the most challenging issues in mining information from the World Wide Web is the design of systems that can present the data to the end user by clustering them into meaningful semantic categories. We envision that the analysis of the results of a Web search can significantly take advantage of advanced graph drawing techniques. In this paper we strengthen our point by describing the visual functionalities of WhatsOnWeb, a meta search clustering engine explicitly designed to make it possible for the user to browse the Web by means of drawings of graphs whose nodes represent clusters of coherent data and whose edges describe semantic relationships between pairs of clusters. A prototype of WhatsOnWeb is available at http://whatsonweb.diei.unipg.it/.