Mining Weighted Association Rules with Lucene Index

Discovery of association rules has been found useful in many applications. With large database, the process of mining association rules is time consuming. The efficiency becomes crucial factor. Weighted association is more meaningful in some application. This paper implements a fast and stable algorithm to mining weighted association rules base on the open source library Lucene. The methods to create index in Lucene and utilization of the index to find weighted frequent itemsets are introduced. Based on apriori algorithm, a weighted association rule mining algorithm is implemented. All the rules can be recommended to customer by searching Lucene Index. Experiment shows that this method is more efficient than general apriori algorithm.