scholarly journals Determining the Core Part of Software Development Curriculum Applying Association Rule Mining on Software Job Ads in Turkey

2016 ◽  
Author(s):  
Ilkay Yelmen ◽  
Metin Zontul
Keyword(s):  
Software Development ◽  
Association Rule ◽  
Association Rule Mining ◽  
Rule Mining ◽  
The Core ◽  
Job Ads ◽  
Core Part

scholarly journals Hedyotis diffusaCombined withScutellaria barbataAre the Core Treatment of Chinese Herbal Medicine Used for Breast Cancer Patients: A Population-Based Study

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Yuan-Chieh Yeh ◽  
Hsing-Yu Chen ◽  
Sien-Hung Yang ◽  
Yi-Hsien Lin ◽  
Jen-Hwey Chiu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Herbal Medicine ◽  
Association Rule ◽  
Association Rule Mining ◽  
Breast Cancer Patients ◽  
Rule Mining ◽  
The Core ◽  
Chinese Herbal ◽  
Hedyotis Diffusa ◽  
Treat Breast Cancer

Traditional Chinese medicine (TCM), which is the most common type of complementary and alternative medicine (CAM) used in Taiwan, is increasingly used to treat patients with breast cancer. However, large-scale studies on the patterns of TCM prescriptions for breast cancer are still lacking. The aim of this study was to determine the core treatment of TCM prescriptions used for breast cancer recorded in the Taiwan National Health Insurance Research Database. TCM visits made for breast cancer in 2008 were identified using ICD-9 codes. The prescriptions obtained at these TCM visits were evaluated using association rule mining to evaluate the combinations of Chinese herbal medicine (CHM) used to treat breast cancer patients. A total of 37,176 prescriptions were made for 4,436 outpatients with breast cancer. Association rule mining and network analysis identifiedHedyotis diffusaplusScutellaria barbataas the most common duplex medicinal (10.9%) used for the core treatment of breast cancer.Jia-Wei-Xiao-Yao-San(19.6%) andHedyotis diffusa(41.9%) were the most commonly prescribed herbal formula (HF) and single herb (SH), respectively. Only 35% of the commonly used CHM had been studied for efficacy. More clinical trials are needed to evaluate the efficacy and safety of these CHM used to treat breast cancer.

scholarly journals An approach to improve the efficiency of apriori algorithm

2015 ◽  
Author(s):  
Sakshi Aggarwal ◽  
Ritu Sindhu
Keyword(s):  
Data Mining ◽  
Association Rule ◽  
Association Rule Mining ◽  
Apriori Algorithm ◽  
Core Concept ◽  
Rule Mining ◽  
Algorithm Efficiency ◽  
The Core ◽  
Database Size

Association rule mining has a great importance in data mining. Apriori is the key algorithm in association rule mining. Many approaches are proposed in past to improve Apriori but the core concept of the algorithm is same i.e. support and confidence of item sets and previous studies finds that classical Apriori is inefficient due to many scans on database. In this paper, we are proposing a method to improve Apriori algorithm efficiency by reducing the database size as well as reducing the time wasted on scanning the transactions.

scholarly journals An approach to improve the efficiency of apriori algorithm

2015 ◽  
Author(s):  
Sakshi Aggarwal ◽  
Ritu Sindhu
Keyword(s):  
Data Mining ◽  
Association Rule ◽  
Association Rule Mining ◽  
Apriori Algorithm ◽  
Core Concept ◽  
Rule Mining ◽  
Algorithm Efficiency ◽  
The Core ◽  
Database Size

Association rule mining has a great importance in data mining. Apriori is the key algorithm in association rule mining. Many approaches are proposed in past to improve Apriori but the core concept of the algorithm is same i.e. support and confidence of item sets and previous studies finds that classical Apriori is inefficient due to many scans on database. In this paper, we are proposing a method to improve Apriori algorithm efficiency by reducing the database size as well as reducing the time wasted on scanning the transactions.

SOFTWARE DEFECT PREDICTION USING INTERTRANSACTION ASSOCIATION RULE MINING

2009 ◽  
Vol 19 (06) ◽  
pp. 747-764 ◽  
Author(s):  
CHING-PAO CHANG ◽  
CHIH-PING CHU
Keyword(s):  
Software Development ◽  
Prediction Model ◽  
Association Rule ◽  
Association Rule Mining ◽  
Rule Mining ◽  
High Severity ◽  
Software Defect ◽  
Novel Approach ◽  
Defect Prevention ◽  
Significant Effort

Reducing the variance between expectation and execution of software processes is an essential activity for software development, in which the Causal Analysis is a conventional means of detecting problems in the software process. However, significant effort may be required to identify the problems of software development. Defect prevention prevents the problems from occurring, thus lowering the effort required in defect detection and correction. The prediction model is a conventional means of predicting the problems of subsequent process actions, where the prediction model can be built from the performed actions. This study proposes a novel approach that applies the Intertransaction Association Rule Mining techniques to the records of performed actions in order to discover the patterns that are likely to cause high severity defects. The discovered patterns can then be applied to predict the subsequent actions that may result in high severity defects.

scholarly journals Model Prediksi Penempatan Magang Siswa SMK menggunakan Teknik Association Rule Mining

2020 ◽  
Vol 9 (1) ◽  
pp. 1-10
Author(s):  
Dwi Welly Sukma Nirad ◽  
Afriyanti Dwi Kartika ◽  
Aghill Tresna Avianto ◽  
Aulia Anshari Fathurrahman
Keyword(s):  
Data Mining ◽  
Student Performance ◽  
Association Rule ◽  
Association Rule Mining ◽  
Vocational School ◽  
Mining Method ◽  
Rule Mining ◽  
The Core ◽  
Data Mining Method ◽  
The Future

Insternship activity is one of the core activities of every Vocational School (SMK) as the purpose of this school is to conduct education at the level of work-oriented readiness. Every SMK graduate is expected to be better prepared to enter the industrial world. However, in fact there were gaps that resulted in the unpreparedness of students after graduating from school. This research identified and analyzed the placement of student internships. The aim was to find an insternship placement pattern in order to get an overview and recommendation of an appropriate internship according to students abilities. The technique used was the association rule mining, a technique of the data mining method that was useful for uncovering the rules that were correlated to each other so that they can better organize and predict the internship placements. The results showed that the association rule mining could be applied to analyze student performance and predict internship placements in the future. This prediction could be a consideration for the teacher to determine the subjects that need to be improved to prepare students for internships.

A Novel Market Basket Analysis Using Adaptive Association Rule Mining Algorithm

2012 ◽  
Vol 1 (4) ◽  
pp. 25-28
Author(s):  
M.Dhanabhakyam M.Dhanabhakyam ◽  
◽  
Dr.M.Punithavalli Dr.M.Punithavalli
Keyword(s):  
Association Rule ◽  
Association Rule Mining ◽  
Market Basket Analysis ◽  
Rule Mining ◽  
Market Basket ◽  
Mining Algorithm

Prediksi Code Defect Perangkat Lunak Dengan Metode Association Rule Mining dan Cumulative Support Thresholds

2015 ◽  
Vol 6 (2) ◽  
Author(s):  
Rizal Setya Perdana ◽  
Umi Laili Yuhana
Keyword(s):  
Association Rule ◽  
Association Rule Mining ◽  
Rule Mining ◽  
Program Code

Kualitas perangkat lunak merupakan salah satu penelitian pada bidangrekayasa perangkat lunak yang memiliki peranan yang cukup besar dalamterbangunnya sistem perangkat lunak yang berkualitas baik. Prediksi defectperangkat lunak yang disebabkan karena terdapat penyimpangan dari prosesspesifikasi atau sesuatu yang mungkin menyebabkan kegagalan dalam operasionaltelah lebih dari 30 tahun menjadi topik riset penelitian. Makalah ini akandifokuskan pada prediksi defect yang terjadi pada kode program (code defect).Metode penanganan permasalahan defect pada kode program akan memanfaatkanpola-pola kode perangkat lunak yang berpotensi menimbulkan defect pada data setNASA untuk memprediksi defect. Metode yang digunakan dalam pencarian polaadalah memanfaatkan Association Rule Mining dengan Cumulative SupportThresholds yang secara otomatis menghasilkan nilai support dan nilai confidencepaling optimal tanpa membutuhkan masukan dari pengguna. Hasil pengujian darihasil pemrediksian defect kode perangkat lunak secara otomatis memiliki nilaiakurasi 82,35%.

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