ResearchPreference Data Management



Picture of Preference Data ManagementPreference data is prevalent variety of domains. The past decade has seen a proliferation in the volume of preference data, the diversity of applications based on preference data, and the richness of preference analysis methods. Examples include rank aggregation in genomic data, management and analysis of elections, and recommendation systems in e-commerce. Management of preference data entails special requirements and opportunities that cast it substantially distinct from general (e.g., relational or graph) data management: certain atomic operations are not supported by standard database engines, yet are very common in preference data analytics; statistical models of preferences fall outside the standard formalisms of “probabilistic databases;” election data requires out-of-databases analysis of the space of outcomes for a given incomplete picture of the voter preferences. Our research develops fundamental frameworks for the management of preference data, with emphasis on the associated complexity and algorithms.


Selected Publications

Batya Kenig, Lovro Ilijasic, Haoyue Ping, Benny Kimelfeld, Julia Stoyanovich, "Probabilistic Inference Over Repeated Insertion Models", AAAI 2018   abstractpaper
Benny Kimelfeld, Phokion G. Kolaitis, Julia Stoyanovich, "Computational Social Choice Meets Databases", IJCAI 2018: 317-323   abstractpaper
Uzi Cohen, Batya Kenig, Haoyue Ping, Benny Kimelfeld, Julia Stoyanovich, "A Query Engine for Probabilistic Preferences", SIGMOD Conference 2018: 1509-1524   abstractpaper
Benny Kimelfeld, Ester Livshits, Liat Peterfreund, "Detecting Ambiguity in Prioritized Database Repairing", ICDT 2017: 17:1-17:20   abstractpaper
Batya Kenig, Benny Kimelfeld, Haoyue Ping, Julia Stoyanovich, "Querying Probabilistic Preferences in Databases", PODS 2017: 21-36   abstractpaper