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10 Feb

As of 2017, Deep Dive project is in maintenance mode and no longer under active development.

The user community remains active, but the original project members can no longer promise exciting new features/improvements or responding to requests.

For the more up-to-date research, please see the Snorkel Project or Ce Zhang's Projects.

Deep Dive is a system to extract value from dark data.

Deep Dive is designed to make it easy for users to train the system through low-level feedback via the Mindtagger interface and rich, structured domain knowledge via rules.Deep Dive is project led by Christopher RĂ© at Stanford University.Current group members include: Michael Cafarella, Xiao Cheng, Raphael Hoffman, Dan Iter, Thomas Palomares, Alex Ratner, Theodoros Rekatsinas, Zifei Shan, Jaeho Shin, Feiran Wang, Sen Wu, and Ce Zhang.Deep Dive is used to extract sophisticated relationships between entities and make inferences about facts involving those entities.Deep Dive helps one process a wide variety of dark data and put the results into a database.