Paper Info
Title
Post Sequential Patterns Mining - A New Method For Discovering Structural Patterns
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.
Year
DOI
Venue
2004
10.1007/0-387-23152-8_31
INTELLIGENT INFORMATION PROCESSING II
Keywords
Field
DocType
post sequential patterns mining, sequential patterns graph, structural pattern, concurrent branch patterns
Data modeling,Graph,Data mining,Computer science
Conference
Volume
ISSN
Citations 
163
1571-5736
0
PageRank 
References 
Authors
0.34
12
4
Name
Order
Citations
PageRank
Jing Lu170.92
Osei Adjei2144.20
Weiru Chen3466.64
Jun Liu410.70