Smart Query Definition for Content-Based Search in Large Sets of Graphs (English)

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Graphs are used in various application areas such as chemical, social or shareholder network analysis. Finding relevant graphs in large graph databases is thereby an important problem. Such search starts with the definition of the query object. Defining the query graph quickly and effectively so that it matches meaningful data in the database is difficult. In this paper, we introduce a system, which guides the user through the process of query graph building. We propose three approaches for graph definition. First, query by example selection starting from an overview of the graph types in the database, second query by sketch combining graph building blocks (i.e., topologic subgraphs) with free graph drawing, and third a combination of both approaches. In all three query definition ways, we support the user with intelligent, data dependent recommendations. It covers the whole spectrum of building parameters such as representative examples, frequent building blocks, or common graph size.

  • Title:
    Smart Query Definition for Content-Based Search in Large Sets of Graphs
  • Author / Creator:
  • Published in:
  • Publisher:
    The Eurographics Association
  • Place of publication:
    Postfach 8043, 38621 Goslar, Germany
  • Year of publication:
    2010
  • Size:
    6 pages
  • ISBN:
  • DOI:
  • Type of media:
    Conference paper
  • Type of material:
    Electronic Resource
  • Language:
    English
  • Source:
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Table of contents conference proceedings

The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.

1
Sensemaking in Visual Analytics: Processes and Challenges
Attfield, Simon J. / Hara, Sukhvinder K. / Wong, B. L. William | 2010
7
Smart Query Definition for Content-Based Search in Large Sets of Graphs
Landesberger, Tatiana von / Bremm, Sebastian / Bernard, Juergen / Schreck, Tobias | 2010
13
Stress Maps: Analysing Local Phenomena in Dimensionality Reduction Based Visualisations
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19
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Pölitz, Christian / Andrienko, Gennady / Andrienko, Natalia | 2010
27
Comparative Visual Analysis of Cross-Linguistic Features
Rohrdantz, Christian / Mayer, Thomas / Butt, Miriam / Plank, Frans / Keim, Daniel A. | 2010
33
Capturing Reasoning Process through User Interaction
Dou, Wenwen / Ribarsky, William / Chang, Remco | 2010
39
Utilizing Treemaps for Multicriterial Search of 3D Objects
Petkos, Georgios / Darlagiannis, Vasilios / Moustakas, Konstantinos / Tzovaras, Dimitrios | 2010
45
Combining Details of the Chi-Square Goodness-of-Fit Test with Multivariate Data Visualization
May, Thorsten / Davey, James / Kohlhammer, Jörn | 2010
51
Policy-making in a Complex World: Can Visual Analytics Help?
Osimo, David / Lampathaki, Fenareti / Charalabidis, Yannis | 2010
57
Visual Analytics to Check Marine Containers in the Eritr\@c Project
Aupetit, Michaël / Allano, Lorène / Espagnon, Isabelle / Sannie, Guillaume | 2010
61
Does Jason Bourne need Visual Analytics to catch the Jackal?
Bertone, Alessio / Lammarsch, Tim / Turic, Thomas / Aigner, Wolfgang / Miksch, Silvia | 2010
69
DYNEVI - DYnamic News Entity Visualization
Wanner, Franz / Schaefer, Matthias / Leitner-Fischer, Florian / Zintgraf, Fabian / Atkinson, M. / Keim, Daniel A. | 2010
75
Visual Analytics in Software Maintenance: Challenges and Opportunities
Telea, Alexandru / Ersoy, Ozan / Voinea, Lucian | 2010
81
Interactive Visual Analysis of Families of Surfaces: An Application to Car Race and Car Setup
Matkovic, Kresimir / Gracanin, Denis / Splechtna, Reiner / Hauser, Helwig | 2010
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