Preference Elicitation for Group Decisions Using the Borda Voting Rule

This paper addresses the issue of preference elicitation for group decision making using voting rules. We propose a general, domain-free framework for preference management, where the goal is to minimize the communication cost with the users. We introduce novel heuristics and show how they can operate under a ranking voting protocol, specifically under the Borda protocol. We suggest an interactive incremental framework where at each step one user is queried for her ranking order of two items. We propose two approaches for heuristics that determine what query to select next (i.e., whom to query regarding what item or items). One heuristic computes the information gain of each potential query. The other heuristic uses the probability distribution of the voters’ preferences to select the candidate most likely to win and the voter that is expected to maximize the score of that item. Both heuristics rely on probabilistic rating distributions. We show how these distributions can be estimated. The rating distributions are updated iteratively, allowing their accuracy to increase over time. We demonstrate the effectiveness of our framework by evaluating the different heuristics on two real-world datasets.