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
In this paper, we give a simple scheme for identifying approximate frequent items over a sliding window of size n. Our scheme is deterministic and does not make any assumption on ...
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...
We present deterministic sub-linear space algorithms for a number of problems over update data streams, including, estimating frequencies of items and ranges, finding approximate ...