Annonce en lien avec l’Action/le Réseau : aucun
Laboratoire/Entreprise : ETIS Lab (ENSEA / UCP / CNRS) UMR 8051, Paris, France
Durée : 3 years
Contact : Dimitrios.Kotzinos@u-cergy.fr
Date limite de publication : 2016-06-01
Contexte :
The MIDI team of the ETIS Lab (ENSEA / UCP / CNRS) UMR 8051 (www-etis.ensea.fr) has available a 3-year fully funded PhD position in the research area of Big Data. The lab is located in the Cergy-Pontoise area in the greater area of Paris, France.
Sujet :
During this PhD we want to investigate crowd sourced Big Data, generated by users who do not follow a well-documented method that could ensure data quality. The quality of these data and their descriptions might vary depending on the source, the type of the metadata included (or the lack thereof) and the person who is referencing them. This problem becomes more evident when we talk about georeferenced crowd sourced data where we are facing problems of completeness of the information (since usually people provide online information that refers to their interests) and the coherence of the information (and thus its semantic quality), including ambiguity or conversion issues. Moreover, we can identify quality issues that can be attributed to the timeliness of the information (since several types information do not disappear over time e.g. social media posts) and of logical consistency (since we can find online conflicting descriptions on e.g. Points of Interest). There is also a heterogeneity in the level of detail of the crowd sourced information because the level of abstraction of the user capturing information is closely related to her interests. Another important question in this area is how the techniques of big data quality enhancement affect the privacy of the users.
Based on the above during this PhD we would like to work on how to:
1. Deal with incompleteness of information by combining information on entities from diverse sources through applying entity resolution (ER) techniques to a large scale, e.g. combining information from social networks, trajectory information on various platforms, crowd-sourced geographical information like Open Street Maps
2. Increase the quality of the data presented to the end user by understanding the repairs that can be introduced at the crowd-sourced platforms
3. Understand the level of information exposed by increasing the quality of information for the user.
Profil du candidat :
We expect the successful applicant to be one of the driving forces behind the group’s research efforts in the areas mentioned above. He/She will join our international research group and work with other groups in the lab as well as with a strong network of national and international collaborators. The successful applicant will work with Professor Dimitris Kotzinos and Assistant Professor Claudia Marinica and will join a group with 3 professors and 5 assistant professors. Knowledge of French is not a requirement.
Starting Date: October 2016
Application: If interested, please send your application (including a detailed CV, university transcripts, a copy of the master thesis or scientific papers if available, as well as a list of personal references and and a motivation letter) in PDF format to Professor Dimitris Kotzinos (Dimitrios.Kotzinos@u-cergy.fr). Further enquiries are also welcome.
Applications are welcome until 25/05/2016 or until the position is filled.
Formation et compétences requises :
The successful candidate should already have a Master or equivalent in Computer Science or related area and should be able to demonstrate the ability to conduct research.
Adresse d’emploi :
Lab. ETIS (ENSEA/UCP/CNRS UMR 8051)
& Dept. Sciences Informatiques, Université de Cergy-Pontoise
2 av. Adolphe Chauvin
Site Saint Martin
95000 Pontoise
France
phone: +33 13425 2855
e-mail: Dimitrios.Kotzinos@u-cergy.fr