The frequent items problem is to process a stream of items and find all items occurring more than a given fraction of the time. It is one of the most heavily studied problems in d...
We consider the problem of maintaining frequency counts for items occurring frequently in the union of multiple distributed data streams. Na?ive methods of combining approximate f...
Amit Manjhi, Vladislav Shkapenyuk, Kedar Dhamdhere...
Abstract. We present novel space and time-efficient algorithms for finding frequent items over general update streams. Our algorithms are based on a novel adaptation of the popula...
Sumit Ganguly, Abhayendra N. Singh, Satyam Shankar
Computing statistical information on probabilistic data has attracted a lot of attention recently, as the data generated from a wide range of data sources are inherently fuzzy or ...