Literature DB >> 17218746

Graph visualization techniques for web clustering engines.

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


  2 in total

1.  A visual sonificated web search clustering engine.

Authors:  Alessio Rugo; Maria Laura Mele; Giuseppe Liotta; Francesco Trotta; Emilio Di Giacomo; Simone Borsci; Stefano Federici
Journal:  Cogn Process       Date:  2009-09

2.  MCLEAN: Multilevel Clustering Exploration As Network.

Authors:  Daniel Alcaide; Jan Aerts
Journal:  PeerJ Comput Sci       Date:  2018-01-29
  2 in total

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