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Communication Dans Un Congrès Année : 2023

PathWays: entity-focused exploration of heterogeneous data graphs

Nelly Barret
Antoine Gauquier
Jia-Jean Law
  • Fonction : Auteur
  • PersonId : 1256025
Ioana Manolescu

Résumé

Graphs, and notably RDF graphs, are a prominent way of sharing data. As data usage democratizes, users need help figuring out the useful content of a graph dataset. In particular, journalists with whom we collaborate [3] are interested in identifying, in a graph, the connections between entities, e.g., people, organizations, emails, etc. We propose PathWays, an interactive tool for exploring data graphs through their data paths connecting Named Entities (NEs, in short); each data path leads to a tabular-looking set of results. NEs are extracted from the data through dedicated Information Extraction modules. PathWays leverages the ConnectionLens platform [4,6] and follow-up work on dataset abstraction [5]. Its novelty lies in its interactive and efficient approach to enumerate, compute, and analyze NE paths.
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hal-04103293 , version 1 (23-05-2023)

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  • HAL Id : hal-04103293 , version 1

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Nelly Barret, Antoine Gauquier, Jia-Jean Law, Ioana Manolescu. PathWays: entity-focused exploration of heterogeneous data graphs. ESWC 2023 - 20th European Semantic Web Conference, May 2023, Hersonissos (Crete), Greece. ⟨hal-04103293⟩
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