ABSTRACT

Data mining is the process to discover probably beneficial definite information from the large transactional databases. Association rule mining is most common technique of data mining. It aims at discovering associations between attributes in the large databases. It is used for various applications and also applies on Wireless Sensors Network (WSN) dataset. It is a difficult task to extract the interesting knowledge from WSN in mining techniques.In this paper, we extract the useful information from WSN dataset by using Associated Sensor Pattern Mining of data Stream (ASPMS) algorithm. For finding the frequent patterns among sensors, we apply three algorithms i.e. Apriori, FP-growth and ASPMS algorithm. Results shows in comparative manner, that our technique is time and storage efficient with less memory scan in finding frequent patterns than Apriori and FP Growth algorithm.