Efficient Single Pass Ordered Incremental Pattern Mining

2013 ◽  
pp. 137-156 ◽  
Author(s):  
Yun Sing Koh ◽  
Gillian Dobbie
Keyword(s):  
Pattern Mining ◽  
Single Pass

Efficient single-pass frequent pattern mining using a prefix-tree

2009 ◽  
Vol 179 (5) ◽  
pp. 559-583 ◽  
Author(s):  
Syed Khairuzzaman Tanbeer ◽  
Chowdhury Farhan Ahmed ◽  
Byeong-Soo Jeong ◽  
Young-Koo Lee
Keyword(s):  
Pattern Mining ◽  
Frequent Pattern Mining ◽  
Frequent Pattern ◽  
Single Pass ◽  
Prefix Tree

CP-Tree: A Tree Structure for Single-Pass Frequent Pattern Mining

2008 ◽  
pp. 1022-1027 ◽  
Author(s):  
Syed Khairuzzaman Tanbeer ◽  
Chowdhury Farhan Ahmed ◽  
Byeong-Soo Jeong ◽  
Young-Koo Lee
Keyword(s):  
Pattern Mining ◽  
Frequent Pattern Mining ◽  
Tree Structure ◽  
Frequent Pattern ◽  
Single Pass

An Adaptive Data Distribution Through Tree Rules in Frequent Pattern Mining

2018 ◽  
pp. 300-305
Keyword(s):  
Information Sharing ◽  
Pattern Mining ◽  
Data Distribution ◽  
Frequent Pattern Mining ◽  
Frequent Pattern ◽  
General Development ◽  
Secure Information ◽  
Evaluation Parameters ◽  
Secure Information Sharing

Information sharing among the associations is a general development in a couple of zones like business headway and exhibiting. As bit of the touchy principles that ought to be kept private may be uncovered and such disclosure of delicate examples may impacts the advantages of the association that have the data. Subsequently the standards which are delicate must be secured before sharing the data. In this paper to give secure information sharing delicate guidelines are bothered first which was found by incessant example tree. Here touchy arrangement of principles are bothered by substitution. This kind of substitution diminishes the hazard and increment the utility of the dataset when contrasted with different techniques. Examination is done on certifiable dataset. Results shows that proposed work is better as appear differently in relation to various past strategies on the introduce of evaluation parameters.

924-P: Pattern Mining of Trajectories of Glucose Values of Continuous Glucose Monitoring System by Artificial Intelligence in Type 2 Diabetes Patients

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 924-P
Author(s):  
MASAKI MAKINO ◽  
RYO YOSHIMOTO ◽  
MIZUHO KONDO-ANDO ◽  
YASUMASA YOSHINO ◽  
IZUMI HIRATSUKA ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Type 2 Diabetes ◽  
Monitoring System ◽  
Continuous Glucose Monitoring ◽  
Pattern Mining ◽  
Glucose Monitoring ◽  
Continuous Glucose Monitoring System ◽  
Diabetes Patients
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