Volume 6 Issue 4 - March 2016

  • 1. Review and analysis of apriori algorithm for association rule mining

    Authors : Shubhangi Patil, Dr Ratnadeep Deshmukh

    Pages : 104-112

    Keywords : Apriori algorithm, frequent itemset mining.

    Abstract :

    Data mining is a computerized technology that uses complicated algorithms to find relationships in large data bases Extensive growth of data gives the motivation to find meaningful patterns among the huge data. Apriori is a classic algorithm for frequent item set mining and association rule learning over transactional databases. Main idea of this algorithm is to find useful patterns between different set of data. The frequent item sets determined by Apriori can be used to determine association rules which highlight general trends in the database. It is a simple algorithm yet having many drawbacks. So many researchers have been contributed for the improvements of this algorithm. This paper does a survey on few good improved approaches of Apriori algorithm. This will be really very helpful for the upcoming researchers to find some new ideas from these approaches.

    Citing this Journal Article :

    Shubhangi Patil, Dr Ratnadeep Deshmukh, "Review and analysis of apriori algorithm for association rule mining", https://www.ijltet.org/journal_details.php?id=899&j_id=2933, Volume 6 Issue 4 - March 2016, 104-112, #ijltetorg