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Wireless Sensor Networks (WSNs) 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. The authors' 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.