Figuring out the User in a Few Steps: Bayesian Multifidelity Active Search with Cokriging

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  • Nikita Klyuchnikov, Skoltech, Russian Federation
  • Davide Mottin
  • Georgia Koutrika, "Athena" Research Center, Greece
  • Emmanuel Müller, University of Bonn, Germany
  • Panagiotis Karras

Can a system discover what a user wants without the user explicitly issuing a query? A recommender system proposes items of potential interest based on past user history. On the other hand, active search incites, and learns from, user feedback, in order to recommend items that meet a user's current tacit interests, hence promises to offer up-to-date recommendations going beyond those of a recommender system. Yet extant active search methods require an overwhelming amount of user input, relying solely on such input for each item they pick. In this paper, we propose MF-ASC, a novel active search mechanism that performs well with minimal user input. MF-ASC combines cheap, low-fidelity evaluations in the style of a recommender system with the user's high-fidelity input, using Gaussian process regression with multiple target variables (cokriging). To our knowledge, this is the first application of cokriging to active search. Our empirical study with synthetic and real-world data shows that MF-ASC outperforms the state of the art in terms of result relevance within a budget of interactions.

Original languageEnglish
Title of host publicationKDD '19: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
Number of pages10
PublisherAssociation for Computing Machinery
Publication yearAug 2019
Publication statusPublished - Aug 2019
Event25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining - Dena’ina Convention Center and William Egan Convention Center, Anchorage, United States
Duration: 4 Aug 20198 Aug 2019
Conference number: 25


Conference25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
LocationDena’ina Convention Center and William Egan Convention Center
LandUnited States

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