Recording the frequency of items in highly skewed data streams is a fundamental and hot
problem in recent years. The literature demonstrates that sketch is the most promising …

Finding top-K frequent items has been a hot topic in data stream processing in recent years,
which has a wide range of applications. However, most of existing sketch algorithms focuses …

Sketch has been widely used in the field of large-scale data stream processing. However,
common fixed-counter algorithms such as Count-Min Sketch have to allocate larger …

High-accuracy real-time data stream estimations are critical for various applications, and
sliding-window-based techniques have attracted wide attention. However, existing solutions …

Batch is an important pattern in data streams, which refers to a group of identical items that
arrive closely. We find that some special batches that arrive periodically are of great value. In …

Finding top-frequent items has been a hot topic in data stream processing with wide-ranging
applications. However, most existing sketch algorithms focus on finding local top-in a single …

Batch is an important pattern in data streams, which refers to a group of identical items that
arrive closely. We find that some special batches that arrive periodically are of great value. In …

Sketch is a probabilistic data structure widely used in various fields due to its high accuracy
under small memory. Designing hierarchical data structures for real-world datasets with high …

Computing set difference cardinalities is a critical task in database optimization, network
management, and anomaly detection. Due to the limited computational and mem-ory …

Many hashing algorithms including minwise hashing (MinHash), one permutation hashing
(OPH), and consistent weighted sampling (CWS) generate integers of B bits. With k hashes …