Conference
A Distributed Frequent Itemset Mining Algorithm Based on Spark
Abstract
Frequent itemset mining is an important step of association rules mining. Traditional frequent itemset mining algorithms have certain limitations. For example Apriori algorithm has to scan the input data repeatedly, which leads to high I/O load and low performance, and the FP-Growth algorithm is limited by the capacity of computer's inner stores because it needs to build a FP-tree and mine frequent itemset on the basis of the FP-tree in memory. …
Authors
Gui F; Ma Y; Zhang F; Liu M; Li F; Shen W; Bai H
Pagination
pp. 271-275
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Publication Date
May 1, 2015
DOI
10.1109/cscwd.2015.7230970
Name of conference
2015 IEEE 19th International Conference on Computer Supported Cooperative Work in Design (CSCWD)