ConnectionLens: Finding Connections Across Heterogeneous Data Sources - Archive ouverte HAL Access content directly
Journal Articles Proceedings of the VLDB Endowment (PVLDB) Year : 2018

ConnectionLens: Finding Connections Across Heterogeneous Data Sources

(1, 2, 3) , (2, 1) , (4, 5) , (3) , (1, 2) , (1)
1
2
3
4
5

Abstract

Nowadays, journalism is facilitated by the existence of large amounts of publicly available digital data sources. In particular , journalists can do investigative work, which typically consists on keyword-based searches over many heterogeneous , independently produced and dynamic data sources, to obtain useful, interconnecting and traceable information. We propose to demonstrate ConnectionLens, a system based on a novel algorithm for keyword search across heterogeneous data sources. Our demonstration scenarios are based on use cases suggested by journalists from the french journal Le Monde, with whom we collaborate.
Fichier principal
Vignette du fichier
connectionLens.pdf (768.02 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01841009 , version 1 (17-07-2018)

Identifiers

Cite

Camille Chanial, Rédouane Dziri, Helena Galhardas, Julien Leblay, Minh-Huong Le Nguyen, et al.. ConnectionLens: Finding Connections Across Heterogeneous Data Sources. Proceedings of the VLDB Endowment (PVLDB), 2018, 11, pp.4. ⟨10.14778/3229863.3236252⟩. ⟨hal-01841009⟩
511 View
412 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More