Ashok Savasere

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Mining for a.ssociation rules between items in a large database of sales transactions has been described as an important database mining problem. In this paper we present an efficient algorithm for mining association rules that is fundamentally different from known algorithms. Compared to previous algorithms, our algorithm not only reduces the I/O overhead(More)
Mining for association rules between items in a large database of sales transactions has been described as an important database mining problem. In this paper we present an eecient algorithm for mining association rules that is fundamentally diierent from known algorithms. Compared to the previous algorithms, our algorithm reduces both CPU and I/O(More)
Mining for association rules is considered an important data mining problem. Many diierent variations of this problem have been described in the literature. In this paper we introduce the problem of mining for negative associations. A naive approach to nding negative associations leads to a very large number of rules with low interest measures. We address(More)
Abst rac t . Mining for association rules between items in a large database of sales transactions is an important database mining problem. However, the algorithms previously reported in the literature apply only to static databases. That is, when more transactions are added, the mining process must start all over again, without taking advantage of the(More)
This paper presents an overview of an ongoing research program, Federated Autonomous Databases, sponsored by Rome Laboratory (US Air Force) and conducted by Honeywell in collaboration with the University of Minnesota and Georgia Institute of Technology. This program is exploratory in nature and is aimed at understanding and solving, within the scope of the(More)
This paper essentially analyses the sequential pattern of mining algorithms. The discovery of Association relationship seeks more attention in data mining due to the constantly increasing amount of data stored in the real application system. Mining for association rules has its usage in several areas of business such as the process of decision making and(More)
The Data Mining refers to extract or mine knowledge from huge volume of data. Association Rule mining is the technique for knowledge discovery. It is a well-known method for discovering correlations between variables in large databases. One of the most famous association rule learning algorithm is Apriori. The Apriori algorithm is based upon candidate set(More)