The prize-winning paper provides a framework to design and analyze algorithms where aggregation of information from multiple data sources is needed, such as in information retrieval and machine learning. In these situations, the threshold algorithm offers a very efficient method for producing a single unified list of the “top k” results from the combined data sources. The threshold algorithm’s elegant mathematical properties and simplicity are particularly suitable for use in middleware, software that is often used to augment computer operating systems that support complex, distributed applications. The authors also introduced the notion of instance optimality, an extremely strong guarantee of performance, and showed that the threshold algorithm is instance optimal. The paper’s groundbreaking results have built a foundation for much follow-on research.
Congratulations to the award recipients and many thanks to the Gödel Prize Committee for this year!