A vector space model for automatic indexing
Communications of the ACM
Expectation Propagation for approximate Bayesian inference
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
Integer optimization by local search: a domain-independent approach
Integer optimization by local search: a domain-independent approach
SubSift web services and workflows for profiling and comparing scientists and their published works
Future Generation Computer Systems
Statistical quality estimation for general crowdsourcing tasks
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
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The SIGKDD'09 Research Track received 537 paper submissions, which were reviewed by a Program Committee of 199 members, and a Senior Program Committee of 22 members. We used techniques from artificial intelligence and data mining to streamline and support this complicated process at three crucial stages: bidding by PC members on papers, assigning papers to reviewers, and calibrating scores obtained from the reviews. In this paper we report on the approaches taken, evaluate how well they worked, and describe some further work done after the conference.