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Post Sequential Patterns Mining

A New Method for Discovering Structural Patterns
  • Jing Lu
  • Osei Adjei
  • Weiru Chen
  • Jun Liu
Conference paper
Part of the IFIP International Federation for Information Processing book series (IFIPAICT, volume 163)

Abstract

In this paper we present a novel data mining technique, known as Post Sequential Patterns Mining, which can be used to discover Structural Patterns. A Structural Pattern is a new pattern, which is composed of sequential patterns, branch patterns or iterative patterns. Sequential patterns mining plays an essential role in many areas and substantial research has been conducted on their analysis and applications. In our previous work [12], we used a simple but efficient Sequential Patterns Graph (SPG) to model the sequential patterns. The task to discover hidden Structural Pattern is based on our previous work and sequential patterns mining, conveniently named Post Sequential Patterns Mining. In this paper, in addition to stating this new mining problem, we define patterns such as branch pattern, iterative pattern, structural pattern, and concentrate on finding concurrent branch pattern. Concurrent branch pattern is thus one of the main forms of structural pattern and will play an important role in event-based data modelling.

Key words

Post Sequential Patterns Mining Sequential Patterns Graph Structural Pattern Concurrent Branch Patterns 

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Copyright information

© International Federation for Information Processing 2005

Authors and Affiliations

  • Jing Lu
    • 1
  • Osei Adjei
    • 2
  • Weiru Chen
    • 1
  • Jun Liu
    • 1
  1. 1.School of Computer Science and TechnologyShenyang Institute of Chemical TechnologyShenyangChina
  2. 2.Deparfmenf of Computing and Information SystemsUniversity of LutonLutonUK

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