EVENT

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Talk on "Integration of Machine Learning with Dempster-Shafer Theory for User Profiling and Recommendation" and "Modelling and aggregating contributions from crowdsourcing platforms using belief function theory"

We are pleased to inform you about the upcoming seminar by Professor Van-Nam Huynh (JAIST) titled : "Integration of Machine Learning with Dempster-Shafer Theory for User Profiling and Recommendation" and by Dr. Constance Thierry (IRISA) titled : "Modelling and aggregating contributions from crowdsourcing platforms using belief function theory" Everyone interested is cordially invited to attend!

Title:

Integration of Machine Learning with Dempster-Shafer Theory for User Profiling and Recommendation

Abstract:

User profiles that represent users' preferences and interests play an important role in many applications of personalization. With the rapid growth of multiple social platforms, there is a critical need for efficient solutions to learn user profiles from the information shared by users on social platforms so as to improve the quality of personalized services in online environments. Developing an efficient solution to the problem of user profile learning is significantly challenging due to difficulty in handling data from multiple sources, in different formats and often associated with uncertainty. In this talk, we will introduce an integrated framework that combines advanced Machine Learning techniques with Dempster-Shafer theory of evidence (DST) for user profiling and recommendation. Two instances of the proposed framework for user profile learning and one instance for multi-criteria collaborative filtering will be demonstrated with experimental results and analysis that show the effectiveness and practicality of the developed methods. Finally, some directions for future research will be highlighted.

Speaker Bio:

Van-Nam Huynh received a Ph.D. degree (1999) in Mathematics from Vietnam Academy of Science and Technology, and a Habilitation degree (2012) in Informatics from Université de Technologie de Compiègne, France. After serving as a lecturer in the Departments of Mathematics and Computer Science at Quy-Nhon University for over ten years, he joined in 2003 the School of Knowledge Science, Japan Advanced Institute of Science and Technology (JAIST), where he rose through the ranks and is currently a Professor. He was a recipient of the postdoctoral fellowship from the Inoue Foundation for Science, Japan, in the fiscal year 2001. He was also an Adjunct Professor at Chiang Mai University, Thailand since 2015, Visiting Professor at NECTEC Thailand in 2019, and Part-time Lecturer at Tsukuba University, Japan during 2011-2015. His current research interests include data mining and machine learning, modeling and reasoning with uncertainty, argumentation, multi-agents, recommender systems, decision analysis, kansei information processing and applications.

Time/Date:

13:30-14:00 July 10th (Wednesday), 2024

Title:

Modelling and aggregating contributions from crowdsourcing platforms using belief function theory

Abstract:

Crowdsourcing is the outsourcing of tasks on platforms dedicated to the field where a crowd of people come to make their contribution. There is a wide range of tasks that can be outsourced, which means that the platforms are diverse. Routine activity crowdsourcing platforms offer simple tasks to which anyone can contribute and receive a micro-payment as a reward. The crowds on these platforms are very diverse, leading to a wide disparity in the quality of the responses obtained. In this talk, we propose an interface that allows contributors to express their responses in greater detail. The contributions collected in this way are then modelled using the theory of belief functions with a view to aggregating them.
Prospects for future research will also be discussed.

Speaker Bio:

As a Associate Professor at the University of Rennes, Dr. Constance Thierry's research focuses on the modeling and analysis of data from imperfect sources of information, using the theory of belief functions. Dr. Constance Thierry teaches computer science at the IUT de Lannion in various subjects (artificial intelligence techniques, databases, analysis...) and at different grades.