Graph-based keyword search in heterogeneous data sources - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2020

Graph-based keyword search in heterogeneous data sources

Abstract

Data journalism is the field of investigative journalism which focuses on digital data by treating them as first-class citizens. Following the trends in human activity, which leaves strong digital traces, data journalism becomes increasingly important. However, as the number and the diversity of data sources increase, heterogeneous data models with different structure, or even no structure at all, need to be considered in query answering. Inspired by our collaboration with Le Monde, a leading French newspaper, we designed a novel query algorithm for exploiting such heterogeneous corpora through keyword search. We model our underlying data as graphs and, given a set of search terms, our algorithm nds links between them within and across the heterogeneous datasets included in the graph. We draw inspiration from prior work on keyword search in structured and unstructured data, which we extend with the data heterogeneity dimension, which makes the keyword search problem computationally harder. We implement our algorithm and we evaluate its performance using synthetic and real-world datasets.
Fichier principal
Vignette du fichier
paper.pdf (1.17 Mo) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-02934277 , version 1 (09-09-2020)

Identifiers

Cite

Angelos Christos Anadiotis, Mhd Yamen Haddad, Ioana Manolescu. Graph-based keyword search in heterogeneous data sources. BDA 2020 - 36ème Conférence sur la Gestion de Données – Principes, Technologies et Applications, Oct 2020, Online, France. ⟨hal-02934277⟩
403 View
260 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More