An efficient algorithm for distributed incremental updating of frequent item-sets on massive database

  • Authors:
  • Jiangtao Qiu;Changjie Tang;Lei Duan;Chuan Li;Shaojie Qiao;Peng Chen;Qihong Liu

  • Affiliations:
  • School of Computer Science, Sichuan University, Chengdu, China;School of Computer Science, Sichuan University, Chengdu, China;School of Computer Science, Sichuan University, Chengdu, China;School of Computer Science, Sichuan University, Chengdu, China;School of Computer Science, Sichuan University, Chengdu, China;School of Computer Science, Sichuan University, Chengdu, China;School of Computer Science, Sichuan University, Chengdu, China

  • Venue:
  • WISE'06 Proceedings of the 7th international conference on Web Information Systems
  • Year:
  • 2006

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Abstract

Incremental updating of frequent item-sets on a database includes three problems. In this paper, these problems are explored when database stores massive data. The main contributions include: (a) introduces the concept of Interesting Support Threshold; (b) proposes Frequent Item-sets Tree (FITr) with compact structure; (c) proposes and implements algorithm FIIU for frequent item-sets incremental updating; (d) in order to further improve performance, proposes the algorithm DFIIU for distributed incremental updating of frequent Item-sets on massive database; (e) gives extensive experiments to show that FIIU and DFIIU algorithms have better performance than traditional algorithm on massive database when the number of items is less.