17 January. 2021
A key feature of personalization is the elicitation and utilization of a user’s preferences to anticipate their future choices. Any form of prompting during the elicitation process, however, might critically affect what information is divulged by the user, suggesting that a passive learning process might be appropriate. On the other hand, theoretical analysis (see https://www.researchgate.net/publication/316279661_Introspective_Forecasting) suggests that passive learning is inappropriate if one wishes to acquire actionable knowledge. The project seeks to reconcile these views by exploring the use of preference elicitation in a real-world setting. Depending on the internship type, the project can be adapted towards identifying a domain in which preference elicitation can be useful and empirically exploring the effectiveness of different learning strategies, or towards the development and analysis of formal elicitation processes that exhibit certain desirable properties.
Empirical evaluation OR software development OR formal analysis OR theoretical machine learning
The main objective of the internship is to reconcile the two seemingly-conflicting requirements for the process of personalization by exploring the use of preference elicitation in a real-world setting. Depending on the background of the intern, the project can be adapted towards identifying a domain in which preference elicitation can be useful and empirically exploring the effectiveness of different learning strategies, or towards the development and analysis of formal elicitation processes that exhibit certain desirable properties