Projet de recherche doctoral numero :8257


Date depot: 10 janvier 2022
Titre: High Quality Knowledge Graphs from recent English, French and German Emergent Trends with the example of COVID-19
Directrice de thèse: Salima BENBERNOU (LIPADE)
Encadrant : Soror SAHRI (LIPADE)
Domaine scientifique: Sciences et technologies de l'information et de la communication
Thématique CNRS : Données et connaissances

Resumé: The position is funded by the Agence Nationale de la Recherche (ANR). The is part of a joint research project with the University of Lübeck (with a focus on creation of knowledge graphs) and Université Paul Sabatier (in Toulouse with a focus on natural language processing). The Phd at Université de Paris will mainly deal with the quality evaluation of knowledge graphs. Our project is concerned with generating high quality knowledge graphs for emerging English, French and German trends. The aim is to get a general overview of the trends, how facts develop across time and languages, and to carry out a high-quality assessment of these facts in enriched knowledge graphs to support further analyzes with meaningful visualizations. Main activities: - Identify and model quality metrics for evaluating the quality of knowledge graphs. - Quality-aware query that ties the knowledge graph quality, and the query answers quality from the analysis/visualization tool. - Propose efficient incremental methods to optimize the quality evaluation process from the KG creation to the data analysis and visualization.

Doctorant.e: Ieng Frédéric