Implementation of Association Rule Mining Algorithms on Distributed Data Processing Platforms

Sesver, Duygu; Tuna, Sabah; Aktaş, Mehmet S.; Kalipsiz, Oya; Kanli, Alper Nebi; Turgut, Umut Orcun

doi:10.1109/ubmk.2019.8907040

Cited by 6 publications

(5 citation statements)

References 15 publications

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“…Müşterilerin gerçekleştirdikleri aktivite verileri üzerinde sıkça tekrar eden birliktelikler tespit edilerek, kampanyalar kapsamında kullanıla bilinen birliktelik kuralları, veriden çıkartılmaktadır. Verideki birlikteliklerin tespit edilmesi için kullanılan algoritmalarının gerçeklemesi literatürde üzerinde güncel olarak çalışılan bir konudur [1][2][3]. Çalışma kapsamında da farklı birliktelik kuralı çıkarma algoritmalarının, büyük veri işleme ve analizi platformları üzerinde gerçeklenerek koşturulmaları üzerinde çalışılmıştır.…”

Section: Literatür Taramasıunclassified

E-Ticaret Siteleri için Kampanya Otomasyonu Tasarlanması ve Geliştirilmesi

Güler,

Yetişkul,

Uluay

et al. 2023

OPRD

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Bu makalede, bireysel ve kurumsal satıcılara, IT alt yapısı olmaksızın, hızlı ve güvenli bir e-ticaret deneyimi sağlamak için geliştirilmesi planlanan Paycell Vitrin projesi detayları ile aktarılmaktadır. Paycell Vitrin platformu ile, birey ve kurumlara kolaylıkla kendi e-ticaret sitelerini kurmalarına olanak sağlamaktadır. Proje kapsamında, Paycell ödeme altyapısı üzerinden ödemelerini gerçekleştiren müşterilere yönelik, kampanyalar (çekiliş hakkı, puan, indirim kuponu v.b.) tanımlanmasına olanak veren, kampanyaların içeriklerine uygun ödeme davranışları gösteren müşterileri gerçek zamanlı olarak tespit edebilen, kampanya kullanımları ile ilgili raporlamalar üretebilen bir kampanya yönetimi otomasyonu yeteneği eklenmesi tasarlanmıştır. Proje kapsamında geliştirilecek yazılım, Paycell ödeme altyapısını ve kampanya yönetimi modüllerini entegre ederek, kullanıcılarına benzersiz bir alışveriş deneyimi sunmayı amaçlamaktadır. Makalede, projenin e-ticaret altyapıları, ödeme sistemleri ve kampanya yönetimi alanlarındaki izlediği yöntemler ve yaklaşımlar anlatılmaktadır. Bu makale, Paycell Vitrin projesi için motivasyonları, uygulanacak metodolojiyi, beklenen faydaları ve değerlendirme yöntemlerini ayrıntılı olarak tartışmakta ve gelecekteki çalışmalar için öneriler sunmaktadır.

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Section: Literatür Taramasıunclassified

E-Ticaret Siteleri için Kampanya Otomasyonu Tasarlanması ve Geliştirilmesi

Güler,

Yetişkul,

Uluay

et al. 2023

OPRD

View full text Add to dashboard Cite

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“…People may have trouble finding items or websites that are more related to their interests due to an abundance of data on the Internet. 41 Association Rule Mining and Sequential Pattern Mining are often utilized to suggest items that individuals may be interested in. On the other hand, these cannot provide results on large amounts of data in a reasonable time.…”

Section: Literature Reviewmentioning

confidence: 99%

“…14 Many different MapReduce methodologies that leverage Hadoop platforms and HDFS are used efficiently to parallelize frequent-item extraction methods. 14,41,43,44 In MapReduce, however, there is a disk I/O bottleneck problem. The RDD architecture was used by Spark to solve this problem.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Unlike these studies, we focus on machine learning workflows for frequent itemsets mining. There exists some studies that focus on using association rule mining 41,44 and sequential pattern mining libraries [56][57][58] of big data processing frameworks for different purposes. Here, we only focus on utilizing association rule mining and sequential pattern mining algorithms for recommendation systems.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Scalable recommendation systems based on finding similar items and sequences

Uzun‐Per

Gurel²,

Can³

et al. 2022

Concurrency and Computation

Self Cite

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The rapid growth in the airline industry, which started in 2009, continued until the COVID-19 era, with the annual number of passengers almost doubling in 10 years. This situation has led to increased competition between airline companies, whose profitability has decreased considerably. They aimed to increase their profitability by making services like seat selection, excess baggage, Wi-Fi access optional under the name of ancillary services. To the best of our knowledge, there is no recommendation system for recommending ancillary services for airline companies. Also, to the best of our knowledge, there is no testing framework to compare recommendation algorithms considering their scalabilities and running times. In this paper, we propose a framework based on Lambda architecture for recommendation systems that run on a big data processing platform. The proposed method utilizes association rule and sequential pattern mining algorithms that are designed for big data processing platforms. To facilitate testing of the proposed method, we implement a prototype application. We conduct an experimental study on the prototype to investigate the performance of the proposed methodology using accuracy, scalability, and latency related performance metrics. The results indicate that the proposed method proves to be useful and has negligible processing overheads.

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“…The technique shows that the suggested algorithm outperforms the current methodology in terms of association rule mining time by approximately 3 to 5 times. For attribute selection algorithms, the system, [13] which is a repository on a broad process control platform, was constructed. The Open Source platform was chosen for the study technique in terms of overall use.…”

Section: Literature Reviewmentioning

confidence: 99%

The Hash base Apriori Technique for Association Rule Mining and Data Sanitization

Jagtap

2022

SMSJ

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Under different circumstances, private information is exposed, and it must be sanitised before even being shared to address privacy issues. Data mining techniques can collect large amounts of data in a short amount of time. The information gathered by the powerful machine learning techniques may identify the most sensitive content, which pertains to an individual or organization. The degree of sensitivity of data belonging to a business or an agency might vary. Only approved individuals and organizations have access to this information. As a result, using access limitations to confirm the security of complicated data is not a complete operation. It can have an impact on the utility of a data mining solution, and the user may be able to re-identify sensitive data. To introduce instruments to find a mechanism for the security of confidential information. Finding ways to secure confidential data by developing data mining tools and procedures that can be applied to databases, despite the fact that this diminishes the data mining results' trust worthiness. We proposed a data sanitization strategy in this article that uses a frequent itemset classification approach with a modified apriori algorithm. The problem is to maintain intelligence information for vital arrangements while preventing the numerous exposures of company rule mining at the same time. Data sanitization strategy is used to perform a thorough investigation of numerous sequential pattern algorithms for ensuring the privacy of large amounts of data. Our research shows that our approach is efficient, scalable, and provides meaningful correction when compared to other methods used in existing systems. Keywords: Association Rule Mining, Classification, Frequent itemset, data privacy, data hiding, rule generation, support, confidence and transactional dataset

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Implementation of Association Rule Mining Algorithms on Distributed Data Processing Platforms

Cited by 6 publications

References 15 publications

E-Ticaret Siteleri için Kampanya Otomasyonu Tasarlanması ve Geliştirilmesi

E-Ticaret Siteleri için Kampanya Otomasyonu Tasarlanması ve Geliştirilmesi

Scalable recommendation systems based on finding similar items and sequences

The Hash base Apriori Technique for Association Rule Mining and Data Sanitization

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