Dr Sondess Missaoui

Research Associate
Department of Theatre, Film, Television & Interactive Media
University of York

Sondess Missaoui is a Research Associate in Artificial Intelligence at the University of York.

Sondess received a master's degree in Artificial Intelligence with a specialty in Decision-Making systems for Business Intelligence from the University of Carthage, and she obtained her Ph.D. in Computer Sciences at the University of Milano Bicocca (Italy).

Sondess’s Doctorate was a part of a European project MOBIDOC, entitled Context-aware approaches for Mobile Search. Her research explored the context-awareness technology for personalized recommendation that adapts its behaviour to the mobile and dynamic context without user’s awareness of the underlying technology.

Her research interests include Information Retrieval and Information Filtering, Natural Language Processing, Deep learning, News Verification & User-centred Artificial Intelligence.

Sondess is currently working on a Google News Initiative-funded project - DMINR, where the main focus is in combating mis/disinformation by designing a novel Human-centred AI tool for news verification. Her role is in exploring information retrieval and deep learning technologies to extract, merge, and monitor data.

Blending journalistic expertise with AI to assist investigative in the processes of information research, gathering, and verification. Sondess is a co-Investigator in "After #AidToo: how can women report abuse?" a project funded by City Global Challenges Research Fund. She a reviewer in ACM and IEEE, interdisciplinary journals and conference series.

Publications

Context-Aware Approaches to Mobile Search
Missaoui, S. (2018)
LOOKER: a mobile, personalized recommender system in the tourism domain based on social media user-generated content. Personal and Ubiquitous Computing, 23(2), 181-197.
Missaoui, S., Kassem, F., Viviani, M., Agostini, A., Faiz, R., & Pasi, G. (2019).
A Preferences Based Approach for Better Comprehension of User Information Needs. In Transactions on Computational Collective Intelligence XVIII (pp. 67-85). Springer, Berlin, Heidelberg
Missaoui, S., & Faiz, R. (2015)
On machine learning and knowledge organisation in Multimedia Information Retrieval. In Proceedings of the 6th biennial conference of the UK Chapter of ISKO International Society for Knowledge Organization (2019). ACM.
MacFarlane, A., Missaoui, S., Frankowska T., S., (2019, June)
How to Blend Journalistic Expertise with Artificial Intelligence for Research and Verifying News Stories? Workshop at the ACM CHI Conference on Human Factors in Computing Systems, CHI
Missaoui, S., Gutierrez-Lopez, M., MacFarlane, A., Makri, S., Porlezza, C., Cooper, G., (May 2019)
Journalists as Design Partners for AI, Workshop at the ACM CHI Conference on Human Factors in Computing Systems, CHI
Gutierrez-Lopez, M., Missaoui, S., Makri, S., MacFarlane, A., Cooper, G., Porlezza, C., (May 2019)
A language modeling approach for the recommendation of tourism-related services. In Proceedings of the Symposium on Applied Computing (pp. 1697-1700). ACM
Missaoui, S., Viviani, M., Faiz, R., & Pasi, G. (2017, April)
A Preferences Based Approach for Better Comprehension of User Information Needs. In Transactions on Computational Collective Intelligence XVIII (pp. 67-85). Springer, Berlin, Heidelberg.
Missaoui, S., & Faiz, R. (2015)