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Conditional heavy hitters: detecting interesting correlations in data streams
2015
The VLDB journal
The notion of heavy hitters-items that make up a large fraction of the population-has been successfully used in a variety of applications across sensor and RFID monitoring, network data analysis, event mining, and more. Yet this notion often fails to capture the semantics we desire when we observe data in the form of correlated pairs. Here, we are interested in items that are conditionally frequent: when a particular item is frequent within the context of its parent item. In this work, we
doi:10.1007/s00778-015-0382-5
fatcat:whbvxxxydja5hfcroew2xcdw2m