@inproceedings{dcfd4180a5da45f5b0b63f88bef8c8a9,
title = "Fuzzy prophet: Parameter exploration in uncertain enterprise scenarios",
abstract = "We present Fuzzy Prophet, a probabilistic database tool for constructing, simulating and analyzing business scenarios with uncertain data. Fuzzy Prophet takes externally defined probability distribution (so called VG-Functions) and a declarative description of a target scenario, and performs Monte Carlo simulation to compute probability distribution of the scenario's outcomes. In addition, Fuzzy Prophet supports parameter optimization,where probabilistic models are parameterized and a large parameter space must be explored to find parameters that optimize or achieve a desired goal. Fuzzy Prophet's key innovation is to use 'fingerprints' that can identify parameter values producing correlated outputs of a user-provided stochastic function and to reuse computations across such values. Fingerprints significantly expedite the process of parameter exploration in offline optimization and interactive what-if exploration tasks.",
keywords = "black box, Monte Carlo, probabilistic database, simulation",
author = "Kennedy, \{Oliver A.\} and Steve Lee and Charles Loboz and Slawek Smyl and Suman Nath",
year = "2011",
doi = "10.1145/1989323.1989482",
language = "English",
isbn = "9781450306614",
series = "Proceedings of the ACM SIGMOD International Conference on Management of Data",
publisher = "Association for Computing Machinery ",
pages = "1303--1305",
booktitle = "Proceedings of SIGMOD 2011 and PODS 2011",
address = "United States",
note = "2011 ACM SIGMOD and 30th PODS 2011 Conference ; Conference date: 12-06-2011 Through 16-06-2011",
}