Social networks and discovery in the enterprise (SaND)
Inbal Ronen, Elad Shahar, et al.
SIGIR 2009
Enterprises often need to assess and manage the risk arising from uncertainty in their data. Such uncertainty is typically modeled as a probability distribution over the uncertain data values, specified by means of a complex (often predictive) stochastic model. The probability distribution over data values leads to a probability distribution over database query results, and risk assessment amounts to exploration of the upper or lower tail of a query-result distribution. In this paper, we extend the Monte Carlo Database System to efficiently obtain a set of samples from the tail of a query-result distribution by adapting recent "Gibbs cloning" ideas from the simulation literature to a database setting. © 2010 VLDB Endowment.
Inbal Ronen, Elad Shahar, et al.
SIGIR 2009
B.K. Boguraev, Mary S. Neff
HICSS 2000
Daniel M. Bikel, Vittorio Castelli
ACL 2008
Hang-Yip Liu, Steffen Schulze, et al.
Proceedings of SPIE - The International Society for Optical Engineering