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Conference papers

Toward Visual Interactive Exploration of Heterogeneous Graphs

Irène Burger 1, 2 Ioana Manolescu 2 Emmanuel Pietriga 3 Fabian Suchanek 4
2 CEDAR - Rich Data Analytics at Cloud Scale
LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau], Inria Saclay - Ile de France
3 ILDA - Interacting with Large Data
Inria Saclay - Ile de France, LRI - Laboratoire de Recherche en Informatique
Abstract : An interesting class of heterogeneous datasets, encountered for instance in data journalism applications, results from the inter-connection of data sources of different data models, ranging from very structured (e.g., relational or graphs) to semistructured (e.g., JSON, HTML, XML) to completely unstructured (text). Such heterogeneous graphs can be exploited e.g., by keyword search, to uncover connection between search keywords [1]. In this paper, we present a vision toward making such graphs easily comprehensible by human users, such as journalists seeking to understand and explore them. Our proposal is twofold: (i) abstracting the graph by recognizing structured entities; this simplifies the graph without information loss; (ii) relying on data visualization techniques to help users grasp the graph contents. Our work in this area continues; we present preliminary encouraging results.
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Submitted on : Thursday, February 6, 2020 - 10:02:38 AM
Last modification on : Friday, January 21, 2022 - 3:12:35 AM
Long-term archiving on: : Thursday, May 7, 2020 - 1:23:30 PM


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  • HAL Id : hal-02468778, version 1


Irène Burger, Ioana Manolescu, Emmanuel Pietriga, Fabian Suchanek. Toward Visual Interactive Exploration of Heterogeneous Graphs. SEAdata 2020 - Workshop on Searching, Exploring and Analyzing Heterogeneous Data in conjunction with EDBT/ICDT, Mar 2020, Copenhagen, Denmark. ⟨hal-02468778⟩



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