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ACS/IEEE International Conference on Computer Systems and Applications (AICCSA'01)
Discovery of Fuzzy Sequential Patterns for Fuzzy Partitions in Quantitative Attributes
Beirut, Lebanon
June 25-June 29
ISBN: 0-7695-1165-1
ASCII Text
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Ruey-Shun Chen, Gwo-Hshiung Tzeng, C.C. Chen, Yi-Chung Hu, "Discovery of Fuzzy Sequential Patterns for Fuzzy Partitions in Quantitative Attributes," Computer Systems and Applications, ACS/IEEE International Conference on, pp. 0144, ACS/IEEE International Conference on Computer Systems and Applications (AICCSA'01), 2001.
 
 
BibTex
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@article{ 10.1109/AICCSA.2001.933967,
author = {Ruey-Shun Chen and Gwo-Hshiung Tzeng and C.C. Chen and Yi-Chung Hu},
title = {Discovery of Fuzzy Sequential Patterns for Fuzzy Partitions in Quantitative Attributes},
journal ={Computer Systems and Applications, ACS/IEEE International Conference on},
volume = {0},
year = {2001},
isbn = {0-7695-1165-1},
pages = {0144},
doi = {http://doi.ieeecomputersociety.org/10.1109/AICCSA.2001.933967},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Computer Systems and Applications, ACS/IEEE International Conference on
TI - Discovery of Fuzzy Sequential Patterns for Fuzzy Partitions in Quantitative Attributes
SN - 0-7695-1165-1
SP
EP
A1 - Ruey-Shun Chen,
A1 - Gwo-Hshiung Tzeng,
A1 - C.C. Chen,
A1 - Yi-Chung Hu,
PY - 2001
KW - Data mining; Database; Fuzzy sequential patterns; Fuzzy partitions; Knowledge acquisition
VL - 0
JA - Computer Systems and Applications, ACS/IEEE International Conference on
ER -
 
Ruey-Shun Chen, National Chiao Tung University
Gwo-Hshiung Tzeng, National Chiao Tung University
C.C. Chen, National Chiao Tung University
Yi-Chung Hu, National Chiao Tung University
Abstract: In this paper, we propose the Fuzzy Grids Based Sequential Patterns Mining Algorithm (FGBSPMA) to generate all fuzzy sequential patterns from relational database. In FGBSPMA, each quantitative attribute is viewed as a linguistic variable, and can be divided into many candidate 1-dim fuzzy grids. FGBSPMA is consisted of two phases: one is to generate all the large 1-fuzzy sequences, the other is to generate all the fuzzy sequential patterns. FGBSPMA is a efficiently fuzzy sequential patterns mining algorithm, because FGBSPMA scans database only once and applies proper operations on rows of tables to generate large fuzzy sequences and fuzzy sequential patterns. An example is given to illustrate a detailed process for mining the fuzzy sequential patterns from a specified relation. From this example, we can show efficiency and usefulness of FGBSPMA.
Index Terms:
Data mining; Database; Fuzzy sequential patterns; Fuzzy partitions; Knowledge acquisition
Citation:
Ruey-Shun Chen, Gwo-Hshiung Tzeng, C.C. Chen, Yi-Chung Hu, "Discovery of Fuzzy Sequential Patterns for Fuzzy Partitions in Quantitative Attributes," aiccsa, pp.0144, ACS/IEEE International Conference on Computer Systems and Applications (AICCSA'01), 2001
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