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  • 标题:A MULTITHREAD, NOVEL PATTERN BASED ALGORITHM FOR FINDING FREQUENT PATTERNS WITH JAGGED ARRAY AND VERTICAL DATA FORMAT
  • 本地全文:下载
  • 作者:P.Sumathi ; S.Murugan ; V.Umadevi
  • 期刊名称:Indian Journal of Computer Science and Engineering
  • 印刷版ISSN:2231-3850
  • 电子版ISSN:0976-5166
  • 出版年度:2021
  • 卷号:12
  • 期号:5
  • 页码:1353-1363
  • DOI:10.21817/indjcse/2021/v12i5/211205078
  • 语种:English
  • 出版社:Engg Journals Publications
  • 摘要:Frequent pattern mining is essential for discovering hidden items from a database with more than a prescribed threshold. Knowing frequent patterns helps us to determine the relationship between the items. Many researchers narrated novel algorithms for sequential frequent itemset mining using a single thread, but still, there is a need for time, memory efficient and scalable one. Therefore, the research study proposed an approach for finding frequent patterns, namely TB-NPF-VDF (Thread Based, Novel Pattern Formations with Vertical Data Format), which uses a new way of generating candidate items to minimize the time. Also, it employs a multithread concept and runs several threads simultaneously, one for each frequent 1-itemset to generate the remaining frequent itemsets for that item. Further, it also employs a jagged array to store the frequent patterns to reduce the memory requirement. The research work has been implemented and tested using four real-time datasets. Further, it has been compared with Matrix-Apriori, VDF and NPF-VDF (without multithread), and the experimental results reveal that TB-NPF-VDF outperforms significantly in terms of runtime and storage.
  • 关键词:Frequent Patterns;Jagged Array;Multithread;Novel Pattern Formation;Vertical Data Format
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