DBSCAN is a well-known density based clustering algorithm capable of discovering arbitrary shaped clusters and eliminating noise data. However, parallelization of DBSCAN is challenging as it exhibits ...

Set similarity joins represent a critical operation in modern data management by efficiently identifying pairs of data objects—typically sets—that exhibit a similarity above a defined threshold. Such ...

In this video, S. Muthukrishnan from Rutgers University presents: Algorithms for Processing Massive Data Streams. In modern systems from web to social networks and security applications, data arrives ...

This new technical paper titled “Symmetric Cryptography on RISC-V: Performance Evaluation of Standardized Algorithms” was published by researchers at Intel, North Arizona University and Google, with ...