Abstract
Abstract: An Item set is an instance format that is hidden beneath the raw data and after mining the database is created to help users make certain decisions to improve their business needs. Most of the previous studiesare carried out in extracting frequently occurring items or patterns and rare patterns are often ignored. Rare patterns are very useful in many areas like fraud detection, underselling products, intrusion attacks on networks, and these rare patterns indicate the user with some interesting detils to overcome and avoidthose problems. This paper proposes a new algorithm, BEAP algorithm, which uses binary representation and detects rare items without compromising speed and reduces memory consumption. From the experimental evaluation the proposed algorithm BEAP has been proved to be more effective and efficientthan the existing algorithms.
Published Version
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