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

dc.contributor.authorLandesberger, Tatiana vonen_US
dc.contributor.authorBremm, Sebastianen_US
dc.contributor.authorBernard, Jürgenen_US
dc.contributor.authorSchreck, Tobiasen_US
dc.contributor.editorJoern Kohlhammer and Daniel Keimen_US
dc.description.abstractGraphs 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.en_US
dc.description.seriesinformationEuroVAST 2010: International Symposium on Visual Analytics Science and Technologyen_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): H.3.1 [Information Systems]: Content Analysis and Indexing-Indexing methods H.3.3 [Information Systems]: Information Search and Retrieval-G.2.2 [ Mathematics of Computing]: Graph Theory-H.5.2 [Information Systems]: User Interfaces-Graphical user interfaces (GUI) I.3.4 [Computing Methodologies]: Graphics Utilities-Graphics editorsen_US
dc.titleSmart Query Definition for Content-Based Search in Large Sets of Graphsen_US
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