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The HyperBagGraph DataEdron: An Enriched Browsing Experience of Datasets

Track: Foundation of Data Science and Engineering
  • Xavier OuvrardEmail author
  • Jean-Marie Le Goff
  • Stéphane Marchand-Maillet
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12011)

Abstract

Traditional verbatim browsers give back information linearly according to a ranking performed by a search engine that may not be optimal for the surfer. The latter may need to assess the pertinence of the information retrieved, particularly when s\(\cdot \)he wants to explore other facets of a multi-facetted information space. Simultaneous facet visualisation can help to gain insights into the information retrieved and call for further refined searches. Facets are potentially heterogeneous co-occurrence networks, built choosing at least one reference type, and modeled by HyperBag-Graphs—families of multisets on a given universe. References allow to navigate inside the dataset and perform visual queries. The approach is illustrated on Arxiv scientific pre-prints searches.

Keywords

Hyper-Bag-Graphs Knowledge discovery Visual queries Information retrieval 

Supplementary material

489954_1_En_30_MOESM1_ESM.mp4 (5.2 mb)
Supplementary material 1 (mp4 5300 KB)

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.CERNMeyrinSwitzerland
  2. 2.University of GenevaCarougeSwitzerland

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