: CQL, Continuous Query Language is suitable for data stream queries. Sometimes it is better if the queries operate on relational databases and data streams simultaneously. The exe...
In recent years, emerging applications introduced new constraints for data mining methods. These constraints are typical of a new kind of data: the data streams. In data stream pro...
The increasing prominence of data streams arising in a wide range of advanced applications such as fraud detection and trend learning has led to the study of online mining of freq...
This paper1 presents an efficient modeling technique for data streams in a dynamic spatiotemporal environment and its suitability for mining developing trends. The streaming data a...
Pervasive information systems give an overview of what digital environments should look like in the future. From a data-centric point of view, traditional databases have to be used...
In this paper, we study the problem of anomaly detection in high-dimensional network streams. We have developed a new technique, called Stream Projected Ouliter deTector (SPOT), t...
Abstract. Data stream mining has become a novel research topic of growing interest in knowledge discovery. Most proposed algorithms for data stream mining assume that each data blo...
Data processing applications for sensor streams have to deal with multiple continuous data streams with inputs arriving at highly variable and unpredictable rates from various sour...
In group communication, users often have different access rights to multiple data streams. Based on the access relation of users and data streams, users can form partially ordered...
In recent years, the management and processing of so-called data streams has become a topic of active research in several fields of computer science such as, e.g., distributed sys...