Improved Apriori Algorithm VIA Frequent Itemsets Prediction

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Provided by: International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE)
Topic: Big Data
Format: PDF
Apriori algorithm is a classical algorithm of association rule mining. It is used to understand what products and services customers tend to purchase at the same time. This classical algorithm is inefficient due to so many scans of database. And if the database is large, it takes too much time to scan the database. Based on this algorithm, this research indicates the limitation of the original Apriori algorithm of wasting time for scanning the whole database searching for the frequent itemsets, and presents an improvement on Apriori by reducing that wasted time depending on scanning the database transactions once to predict the frequent pattern with different itemset sizes.
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