Context-Aware Approaches to Mobile Search
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
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.
A Preferences Based Approach for Better Comprehension of User Information Needs. In Transactions on Computational Collective Intelligence XVIII (pp. 67-85). Springer, Berlin, Heidelberg
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.
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
Journalists as Design Partners for AI, Workshop at the ACM CHI Conference on Human Factors in Computing Systems, CHI
A language modeling approach for the recommendation of tourism-related services. In Proceedings of the Symposium on Applied Computing (pp. 1697-1700). ACM
We are the Change that we Seek: Information Interactions During a Change of Viewpoint. In Proceedings of the 2020 Conference on Human Information Interaction and Retrieval.
AI should embody our values: Investigating journalistic values to inform AI technology design. In Proceedings of the 11th Nordic Conference on Human-Computer Interaction: Shaping Experiences, Shaping Society (pp. 1-13)