Offre en lien avec l’Action/le Réseau : – — –/– — –

Laboratoire/Entreprise : LAMSADE – PSL Research University – Universit{
Durée : 3 ans
Contact : maude.manouvrier@lamsade.dauphine.fr
Date limite de publication : 2023-04-15

Contexte :
Knowledge graphs are gaining ground as a means of encapsulating and sharing domain knowledge. Large companies,
such as Amazon, Bosch, Google, Microsoft and Zalando, have already adopted knowledge graphs to represent and store
their knowledge bases. In addition to enabling the sharing, querying and retrieval of facts of interest to a business or
community, knowledge graphs have recently gained recognition and are becoming the backbone of cognitive artificial
intelligence. Gartner predicts that the application of knowledge graphs and graph mining will grow by 100% per year to
enable more complex and adaptive data science.

Sujet :
In the context of this thesis, we will focus on RDF knowledge graphs, probably the most widely used class of knowledge
graphs. A number of problems arise when managing these knowledge graphs, ranging from their construction to their
exploration and exploitation. We will mainly focus on the management of dynamic knowledge graphs. Indeed, knowledge
is intrinsically dynamic: the sources that feed the knowledge graph can undergo changes that have an impact on the
knowledge graph itself. Moreover, new promising sources can be added to the list of sources used to enrich the knowledge
graph, and other sources that are no longer relevant can be dropped, which in turn has an impact on the facts (nodes and
relations) composing the knowledge graph. The general objective of the thesis is therefore: To design new solutions to
assist knowledge graph providers and users to better handle the effects of dynamic knowledge graphs.
To achieve the above goal, a number of tasks will be undertaken, from state of the art review to design and implementation
of algorithmic solutions to:
1. Characterize the changes a knowledge graph, may undergo,
2. Identify the maintenance actions that can be undertaken to smoothly manage these changes, and
3. Assess and manage the impact on the applications that utilize the knowledge graph.

A 3-year fully funded PhD scholarship is proposed.
An internship is also possible on the same project (April to August 2023) – see http://www.madics.fr/event/offre983/

Profil du candidat :
Interested candidates are invited to send the following to khalid.belhajjame@dauphine.fr and maude.manouvrier@lamsade.dauphine.fr:
– academic CV
– academic transcripts of BSc and MSc
– one page motivation letter explaining why the candidate is suitable for the position
– contact details of two referees

Formation et compétences requises :
Master in Data or Computer Science or equivalent.
Solid skills in databases and knowledge graphs are required.
A good knowledge in algorithmic, programming and machine learning is appreciated.A good knowledge in algorithmic, programming and machine learning is appreciated.

Adresse d’emploi :
Paris Dauphine University, located in the city of Paris, and member of PSL (Paris Sciences et Lettres).

Document attaché : 202302211043_ManagingDynamicKnowledgeGraphs_PhDPositionParisDauphineLamsade.pdf