While traditional database systems optimize for performance on one-shot queries, emerging large-scale monitoring applications require continuous tracking of complex aggregates and...
Graham Cormode, Minos N. Garofalakis, S. Muthukris...
Burst detection is the activity of finding abnormal aggregates in data streams. Such aggregates are based on sliding windows over data streams. In some applications, we want to mo...
In this paper we focus on the following problem in information management: given a large collection of recorded information and some knowledge of the process that is generating th...
Multi-relational data mining has become popular due to the limitations of propositional problem definition in structured domains and the tendency of storing data in relational dat...
Yusuf Kavurucu, Pinar Senkul, Ismail Hakki Toroslu
In this paper, we present a new voting-based object labeling method that is robust to background clutter. The conventional simple voting method shows very poor performance under c...