Efficient Pattern Mining for Wireless Sensor Networks Data

Abstract

Wireless Sensor Networks generate a large amount of data in the form of streams. Mining association rules on the sensor data provides useful information for different applications. In this paper, a total from partial (TFP) tree based approach is used to generate the set of all association rules from data. Our experimental results show that TFP techniques perform better result in case of sparse dataset and significantly comparable as SP-tree approach for the dense dataset.

Keywords: Association Rule Mining; Wireless Sensor Networks; Frequent Pattern.