Comparative Study of Association Rule Mining for Sensor Data
Manisha Rajpoot, Lokesh Kumar Sharma · 2011
Knowledge discovery from sensor data is an emerging research area due to many applications of crucial importance to our society. Wireless Sensor Networks produce large scale of data in the form of streams. Association Rule Mining in the sensor data provides useful information for different applications. In this study we analyze the framework of association rule mining for sensor data. Three data mining techniques PLT, SP-Tree and FP-Growth to mine the sensor data are considered in this study. These techniques are experimented with various support values and number of messages. The comparative performance analyses are reported in this paper.