Temporal Association Rules Mining in T-databases Using Pipeline Technique

2011 ◽  
Author(s):  
Kanhaiya Lal ◽  
N.C. Mahanti
Keyword(s):  
Association Rules ◽  
Temporal Association ◽  
Association Rules Mining

Period Table Based Spatio-temporal Association Rules Mining

2011 ◽  
Vol 13 (4) ◽  
pp. 455-464
Author(s):  
Siyue CHAI ◽  
Fenzhen SU ◽  
Chenghu ZHOU
Keyword(s):  
Association Rules ◽  
Temporal Association ◽  
Association Rules Mining ◽  
Spatio Temporal

A hybrid temporal association rules mining method for traffic congestion prediction

2019 ◽  
Vol 130 ◽  
pp. 779-787 ◽  
Author(s):  
Feng Wen ◽  
Guo Zhang ◽  
Lingfeng Sun ◽  
Xingqiao Wang ◽  
Xiaowei Xu
Keyword(s):  
Association Rules ◽  
Traffic Congestion ◽  
Temporal Association ◽  
Mining Method ◽  
Association Rules Mining ◽  
Congestion Prediction

scholarly journals Pembentukan Temporal Association Rules Menggunakan Algoritma Apriori (Studi Kasus:Toko Batik Diyan Solo)

2016 ◽  
Vol 10 (1) ◽  
pp. 71
Author(s):  
Annisa Mauliani ◽  
Sri Hartati ◽  
Aina Musdholifah
Keyword(s):  
Decision Support ◽  
Association Rules ◽  
Temporal Association ◽  
Apriori Algorithm ◽  
Association Rules Mining

In this study the adding of time aspect on association rules mining result was used. The aspect of time that was used in this study was date of transactions. The information that was resulted from time aspect adding in association rules mining was known as temporal association rules mining..            In this study, Apriori Algorithm was used for the forming of temporal association rules. This result which show Algorithm Apriori and Temporal Association Rules can be used to get more information about Temporal Association Rules. The Result of this examination can be used for decision support for manager. Because the result of Temporal Association Rules have explanation about event. So from the result of Temporal Association Rules can be knowing, the Temporal Association Rules happened at the time of event.In Ramadan Idul Fitri 2013 and Ramadan Idul Fitri 2014 with parameter assess minsup 10%, mintempsup 5, minconf 50%, resulting different Temporal Association Rules. In Ramadan Idul Fitri 2013, no resulting Temporal Association Rules. While is on Ramadan Idul Fitri 2014 resulting Temporal Association Rules with the biggest value of support 14%, that is {BLBP} à  {HPCK}.

Using Association Rules Mining to Characterize of Loss of Control Eating in Childhood

Appetite ◽  
2021 ◽  
pp. 105236
Author(s):  
Alaina L. Pearce ◽  
Timothy R. Brick ◽  
Travis Masterson ◽  
Shana Adise ◽  
S. Nicole Fearnbach ◽  
...  
Keyword(s):  
Association Rules ◽  
Loss Of Control ◽  
Loss Of Control Eating ◽  
Association Rules Mining
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