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3 articles for “candidate itemsets”
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Data Mining Made Simple by A priori Algorithm for Market Analysis
Abstract: Data mining and data warehousing are increasingly becoming popular among IT professionals, academics and researchers from different disciplines. Business enterprises, small, medium or large scale, are considering the deployment of a warehouse as a major step and as a matter of pride. Data mining or knowledge discovery in data bases combines the techniques from mathematics, statistics, algorithms and artificial intelligence to extract the knowledge. Data mining is a main phase …
Published in Current Trends in Information Technology · Vol. 3, Issue 3, 2013 · pp. 1–4 Read article
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Parallelizing Apriori Algorithm using Open MP
Abstract: An Association rule mining used for finding frequent item sets thus generating rules from the frequent item sets. Finding frequent itemsets is more expensive in terms of CPU power and computing resources utilization. Apriori Algorithm is used for high dimensionality on massively large data sets. Parallelism reduces the time required for serial processing. Parallel computing can be applied for mining of association rules. Parallel apriori algorithm focus on parallelizing the …
Published in Recent Trends in Parallel Computing · Vol. 1, Issue 1, 2014 · pp. 1–5 Read article
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A Study of Mining High Utility Itemset
Abstract: Cost effective exploitation of a transactional database refers to the procedure of choosing the transaction sets with most cost effective features that will improve overall incomes of a company. A plethora of data mining algorithms have been recommended in the past few years to focus on mining item sets with high utility value. The word utility is about that feature of item-sets. Thus, mining algorithms tries to find out all …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 2, Issue 3, 2015 · pp. 21–25 Read article