scholarly journals Dynamic Memory Efficient Frequent Pattern Growth for Data Excavation

2017 ◽  
Vol 179 (7) ◽  
pp. 32-40
Author(s):  
G. Gunasekaran ◽  
S. Murugan
Keyword(s):  
Frequent Pattern ◽  
Dynamic Memory ◽  
Pattern Growth ◽  
Memory Efficient

An Anonymous Email Identification Solution based on Writing Structural Patterns

2015 ◽  
Vol 7 (2) ◽  
pp. 37-49
Author(s):  
Yanhua Liu ◽  
Guolong Chen ◽  
Yiyun Zhang
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Digital Forensics ◽  
Frequent Pattern ◽  
Analytic Hierarchy ◽  
Structural Pattern ◽  
Structural Patterns ◽  
Pattern Growth ◽  
Weight Calculation ◽  
Hierarchy Process

A method to analyze anonymous emails in digital forensics is presented in this paper. The frequent pattern-growth algorithm is used in the proposed method to analyze an email and obtain the structural email writing pattern of the user. The influence of a user's writing structural pattern on the analysis of an anonymous email varies. The analytic hierarchy process is used to calculate the weight of a user's different writing structural patterns. For a given anonymous email, matching the writing structural pattern and weight calculation can help investigators improve their decision making and determine the author of an anonymous email in forensic work.

scholarly journals Marketing Strategy Using Frequent Pattern Growth

2021 ◽  
Vol 3 (2) ◽  
pp. 194-201
Author(s):  
Nazori Suhandi ◽  
Rendra Gustriansyah
Keyword(s):  
Association Rules ◽  
Marketing Strategies ◽  
Frequent Pattern ◽  
High Positive Correlation ◽  
Pattern Growth ◽  
Growth Method ◽  
Mining Methods ◽  
The Right ◽  
The Impact

The biggest problem faced by printing companies during the Covid-19 pandemic was that the number of orders was unstable and tends to decrease, which had the potential to harm the company. Therefore, various appropriate marketing strategies were needed so that the number of product orders was relatively stable and even increases. The impact was that the company could survive and continued to grow. This study aimed to assist company managers in developing appropriate marketing strategies based on association rules generated from one of the data mining methods, namely the Frequent Pattern Growth (FP-Growth) method. The case study of this research was a printing company where there was no similar research that used a printing company's dataset. This study produced nine association rules that meet a minimum of 25% support and a minimum of 60% confidence, but only two association rules that had a high positive correlation, namely for a custom paper bag and banner products. Therefore, several marketing strategies were suggested that could be used as guidelines for companies in managing sales packages and giving special discounts on a product. The results of this study are expected to trigger an increase in the number of product orders because this study tried to find the right product for consumers and did not try to find the right consumers for a product.

scholarly journals Penerapan Data Mining Untuk Analisa Pola Pembelian Produk Menggunakan Algoritma Frequent Pattern – Growth

Rekayasa ◽  
2022 ◽  
Vol 14 (3) ◽  
pp. 456-460
Author(s):  
Paisal Soleh ◽  
Abu Tholib ◽  
M. Noer Fadli Hidayat
Keyword(s):  
Data Mining ◽  
Frequent Pattern ◽  
Pattern Growth
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