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Graph visualization techniques for web clustering engines.

Emilio Di Giacomo·Walter Didimo·Luca Grilli·Giuseppe Liotta
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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.

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AlgorithmsCluster AnalysisComputer GraphicsDatabase Management SystemsDatabases, FactualInformation DisseminationInformation Storage and RetrievalInternetPattern Recognition, AutomatedSemanticsUser-Computer InterfaceEvaluation StudyJournal Article

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Emilio Di Giacomo, Walter Didimo, Luca Grilli, Giuseppe Liotta. Graph visualization techniques for web clustering engines.. https://doi.org/10.1109/tvcg.2007.40

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