Mining Frequent Itemsets From Uncertain Databases Using Probabilistic Support
Mining of frequent itemsets is one of the popular knowledge discovery and data mining tasks. The frequent itemset mining algorithms find itemsets from traditional transaction databases, in which the content of each transaction i.e. items is definitely known and precise. There are many real-life applications like location-based services, sensor monitoring systems in which the content of transactions is uncertain. This initiates the requirement of uncertain data mining. The frequent itemset mining in uncertain transaction databases semantically and computationally differs from traditional techniques applied to standard certain transaction databases.