Background/IntroductionAssociationrule learning is a technique to discover the relations between variables in hugedatabase.
It used to form horizontally distributed databases located in centralizeddatabase. Association rule is found based on low speed of data retrieval thatcaused by centralized database server served for all side of databasesimultaneously. Thus, “association rule helps to group the data into smallfragments and stored at distinct site of computer”.
It also brings benefit ofimproving availability of the database to 24/7h and maintain the normalisationof the database simultaneously 1. The most usefulness of the technique is tospeed up the data retrieval and reduce timing required to load into database.Mining association rule is an advanced technique to measure the rule ofinterestingness. Algorithm will be used for the technique is Apriori algorithm whichcomply with the principle of all of the subset of a frequent itemset indatabase must be frequent and could use if-then statement to calculate thefrequent itemset with corresponding subsets. Association rule learning is an alternativeprotocol improve simplicity, efficiency and privacy of the subset at which enhancessecurity of computation of the subset 2. TheoryHorizontallydistributed database could use association rule to subdivide the data into fourmodules.
Huge data will be subdividing into user module, administrator module,association rule and Apriori Algorithm. In User module, there have two settingto be considered, that are data owner and data miner could not share same dataand several parties share same data. First setting applies data perturbation tohide and protect data from being snatch by data miner.
Second setting requiresdata mining to have protection to data from other parties. Administrator moduleis a module for admin to view user details based on user processing details. Thirdmodule is association rules that applied to horizontally distributed database toidentify relations between data based on if/then statement. Last module,Apriori algorithm make use for finding association between data fragments especiallydatabases that containing transaction.Literature ReviewThere are a few references that has been reviewed andused in this article. Sayad Shujaubuddin SameerThe paper discussing about the security applied onsensitive data using association rule is very importance in aspect data miningand other learning techniques. In the future, privacy will emphasize on data mining due toproductive of development of data mining.
Rakesh Agrawal and Ramkrishnan ShrikantThe paper review on fast algorithm could be applied ondistribution database for mining association rules purpose on various computerwithin a network 3. Bar-code technology or known as basket data able to collectand store huge data by retail organizations through the rules.M.saraaswati and N. KowsalyaThe paper discussing on privacy preserving and datasecure mining of association rule in distributed rule 1. Apriori algorithm alreadyapplied on most of parallel and distributed ARM algorithm but directly applyApriori algorithm won’t obviously improve the performance of distributed ARM. The result outcome/contributionAssociation rule should be able toimprove the performance of data distribution in the aspect of computation time.Testing should be conduct with constant of size of data with dynamic elementswithin each data.
The output should have constant changing of estimated timeinversely proportional to element size. ConclusionAssociation rules applied inhorizontally distributed databases can improve the privacy and efficiency comparedto current leading protocol. Association of algorithm with association rule isa high secure multi-party protocol that could use to computing the subset ofdata that involve various parties. The module also tests for performance ofdata held by different person. Problems on data performance at different side justcan be found when the players involved is more than two.