Many real-time applications, such as traffic control systems, surveillance systems and health monitoring systems, need to operate on continuous unbounded streams of data. These ap...
Incremental mining of sequential patterns from data streams is one of the most challenging problems in mining data streams. However, previous work of mining sequential patterns fr...
Sensor devices are becoming ubiquitous, especially in measurement and monitoring applications. Because of the real-time, append-only and semi-infinite natures of the generated se...
Mohamed G. Elfeky, Walid G. Aref, Ahmed K. Elmagar...
A top-k query retrieves the k highest scoring tuples from a data set with respect to a scoring function defined on the attributes of a tuple. The efficient evaluation of top-k q...
Gautam Das, Dimitrios Gunopulos, Nick Koudas, Niko...
In many applications, stream data are too voluminous to be collected in a central fashion and often transmitted on a distributed network. In this paper, we focus on the outlier det...
Liang Su, Weihong Han, Shuqiang Yang, Peng Zou, Ya...
Abstract. We develop a practical, distributed algorithm to detect events, identify measurement errors, and infer missing readings in ecological applications of wireless sensor netw...
Data streams are modeled as infinite or finite sequences of data elements coming from an arbitrary but fixed universe. The universe can have various built-in functions and predi...
We address the problem of sketching the hamming distance of data streams. We present a new notion of sketching technique, Fixable sketches and we show that using such sketch not o...
In this work a method for detecting distance-based outliers in data streams is presented. We deal with the sliding window model, where outlier queries are performed in order to de...
Sequential pattern mining is an active field in the domain of knowledge discovery. Recently, with the constant progress in hardware technologies, real-world databases tend to gro...