An Application of Apriori Algorithms for Finding Frequent Itemsets in Pharmacy Database to Find Frequent Medicine Itemsets |
Author(s): |
| V. Pusphalatha , kMM Institute of PG Studies; Mr. J. S Ananda Kumar, kMM Institute of PG Studies |
Keywords: |
| Association Rules, Persistent Pattern, Data Mining |
Abstract |
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Apriori algorithm has been successfully used for finding the persistent item sets in huge databases. In this paper study about finding associations between item sets contains data about diagnosis and treatment. It has shown that the algorithm is equally beneficent for finding the large item sets and thus generating the association rules in transactional databases. Healthcare is a data rich domain so we have applied Apriori algorithm for medical practices, insurance companies and other health related organizations that have collected huge volumes of data, thus attracting data mining researchers to explore it and find something beneficent from it. |
Other Details |
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Paper ID: IJSRDV7I10548 Published in: Volume : 7, Issue : 1 Publication Date: 01/04/2019 Page(s): 926-928 |
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