With the advent of World Wide Web, automated tools have become necessary for users to find the required information and also for analysing usage patterns.
Association rule mining is a data mining technique which was used previously; later ODAM algorithm was proposed which is a distributed algorithm for geographically distributed data which has reduced communication costs. Recently Distributed association rule mining was developed for distributed data bases but it does not work in case of high-order association rules between textual documents.
In the existing systems data mining algorithms can be classified as Association algorithm, classification and clustering algorithm. Wherein classification is division of dataset into mutually exclusive groups where the members are close to each other and groups are far from other groups and the distance is measured by specific variables you predict.
Where clustering means division of dataset into mutually exclusive groups where the members are close to each other and groups are far from other groups and the distance is measured by all variables.
In the proposed system ODAM provides better performance when compared to other algorithms by focussing on both communication and synchronization. The paper is about mining techniques used in order to meet the present situations. It gives various techniques of mining and introduces Association rule mining as mining technique. And in detail description was given and also its features and also its advantages when compared to other techniques is discussed and concluded that ODAM has better performance when compared to other algorithms.
Software Requirements include
Operating System – Windows XP/2000
Language used – J2sdk1.4.0, JCreator
Hardware Requirements include
Processor : Intel Processor IV
RAM : 128 MB
Hard disk : 20 GB.
Download ODAM An Optimized Distributed Association Rule Mining Algorithm Project Abstract.