UF-evolve: Uncertain frequent pattern mining

Shu Wang, Vincent To Yee Ng

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)


Many frequent-pattern mining algorithms were designed to handle precise data, such as the FP-tree structure and the FP-growth algorithm. In data mining research, attention has been turned to mining frequent patterns in uncertain data recently. We want frequent-pattern mining algorithms for handling uncertain data. A common way to represent the uncertainty of a data item in record databases is to associate it with an existential probability. In this paper, we propose a novel uncertain-frequent-pattern discover structure, the mUF-tree, for storing summarized and uncertain information about frequent patterns. With the mUF-tree, the UF-Evolve algorithm can utilize the shuffling and merging techniques to generate iterative versions of it. Our main purpose is to discover new uncertain frequent patterns from iterative versions of the mUF-tree. Our preliminary performance study shows that the UF-Evolve algorithm is efficient and scalable for mining additional uncertain frequent patterns with different sizes of uncertain databases.
Original languageEnglish
Title of host publicationEnterprise Information Systems - 13th International Conference, ICEIS 2011, Revised Selected Papers
PublisherSpringer Verlag
Number of pages19
ISBN (Print)9783642299575
Publication statusPublished - 1 Jan 2012
Event13th International Conference on Enterprise Information Systems, ICEIS 2011 - Beijing, China
Duration: 8 Jun 201111 Jun 2011

Publication series

NameLecture Notes in Business Information Processing
Volume102 LNBIP
ISSN (Print)1865-1348


Conference13th International Conference on Enterprise Information Systems, ICEIS 2011


  • Merging
  • Shuffling
  • Tree
  • Uncertain frequent pattern mining

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Management Information Systems
  • Business and International Management
  • Information Systems
  • Modelling and Simulation
  • Information Systems and Management


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