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Research ArticleOpen accessEvery word in the titleTowards a Generic Multimodal Architecture for Batch and Streaming Big Data IntegrationSiham Yousfi, Maryem Rhanoui, Dalila ChiadmiBig Data are rapidly produced from various heterogeneous data sources. They are of different types (text, image, video or audio) and have different levels of reliability and completeness. One of the most interesting architectures that deal with the large amount of emerging data at high velocity is called the lambda architecture. In fact, it combines two different processing layers namely … …Journal of Computer Science, Vol. 15, Issue 1 · 31 Jan 2019 · 7,646 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleIntegrating Data Mining Methods Across all Domains of a Smart CityRushit Dave, Nuo Xu, Simon Arneberg et al.As modern cities continue to develop, smart devices are being used to improve citizens’ lives. As these devices become more sophisticated, the amount of information that they collect increases. A Smart City is a city that uses a large amount of generated data to constantly improve the services offered to the people that live there. Data mining techniques can be … …Journal of Computer Science, Vol. 18, Issue 5 · 30 May 2022 · 7,075 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleClassify Breast Cancer Patients using Hybrid Data-Mining TechniquesFaris E. Mohammed, Nadia Smaoui Zghal, Dalinda Ben Aissa, Mostafa Mahmoud El-GayarAccording to the World Health Organization (WHO), breast cancer is a disease that leads to death, especially for women who have neglected or ignored the risk factors. Doctors can classify patients according to clinical information, famous disease symptoms, or similar cases. But, some cases are difficult to detect early or diagnose accurately. Therefore, the most important challenge faced by researchers … …Journal of Computer Science, Vol. 18, Issue 4 · 12 May 2022 · 6,526 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA User-Driven Association Rule Mining Based on Templates for Multi-Relational DataCarlos Roberto Valêncio, Guilherme Henrique Morais, Márcio Zamboti Fortes et al.Data mining algorithms to find association rules are an important tool to extract knowledge from databases. However, these algorithms produce an enormous amount of rules, many of which could be redundant or irrelevant for a specific decision-making process. Also, the use of previous knowledge and hypothesis are not considered by these algorithms. On the other hand, most existing data mining … …Journal of Computer Science, Vol. 14, Issue 11 · 8 Nov 2018 · 7,442 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleHealthcare Driven by Big Data AnalyticsCheryl Ann Alexander, Lidong WangText messages and social network posts are often included in big data and are frequently invaluable sources of health data. When machine learning or data mining is used, it is important to perform an automatic process for integrating all available and related health data. Artificial Neural Network (ANN) is one of the machine learning methods flexible in using algorithms to … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 3 · 28 Sep 2018 · 7,398 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Survey on Recent Applications of Machine Learning with Big Data in Additive Manufacturing IndustryMicheal Omotayo Alabi, Ken Nixon, Ionel BotefAdditive Manufacturing (AM) which is also known as 3D printing technology; is recognized as a new paradigm for manufacturing industry. Additive manufacturing is rapidly expanding across different sectors such as healthcare, electronics, automotive, science and engineering, education, dental, etc. Machine Learning and Big Data are both emerging technologies which are becoming popular and gaining more attention from the industries and … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 3 · 14 Jul 2018 · 10,279 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAn ADD-Oriented Software Architecture for Structuring Information to Open Government DataAndreiwid Sheffer Correa, P. L.P. Correa, F. S.C. Silva, T. CarvalhoThe huge number of heterogeneous and not standardized websites where public records are disclosed is an evidence of how unprepa¬red governments are about Open Government Data movement. This scenario is seen all over the world, especially in organizations which open data prin¬ciples are new e.g. local governments. Thus, not effective law enforcement and the lack of openness result in a … …Journal of Computer Science, Vol. 14, Issue 5 · 10 Mar 2018 · 7,633 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Reformed K-Nearest Neighbors Algorithm for Big Data SetsVo Ngoc Phu, Vo Thi Ngoc TranA Data Mining Has Already Had Many Algorithms Which A K-Nearest Neighbors Algorithm, K-NN, Is A Famous Algorithm For Researchers. K-NN Is Very Effective On Small Data Sets, However It Takes A Lot Of Time To Run On Big Datasets. Today, Data Sets Often Have Millions Of Data Records, Hence, It Is Difficult To Implement K-NN On Big Data. In … …Journal of Computer Science, Vol. 14, Issue 9 · 8 Mar 2018 · 7,473 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleSecurity Threats to Databases in E-Commerce Systems: A Systematic Literature ReviewNurayn Mesfer AlqahtaniData is a primary by-product of each business. A typical business organization uses a database system to store and manage data. On the other hand, databases are the primary target of hackers and attackers. The existing literature shows that modern database systems are vulnerable to various data breaches, cyberattacks, or malware attacks. Modern business organizations and e-commerce owners look to … …Journal of Computer Science, Vol. 21, Issue 1 · 2 Dec 2024 · 7,291 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleNon-Hodgkin Lymphoma Risk Grading Through the Pathological Data by Using the Optimized Convolutional Lymphnet ModelSivaranjini Nagarajan, Gomathi MuthuswamyDiagnosing Non-Hodgkin Lymphoma (NHL) is difficult and often requires specialised training and expertise as well as extensive morphological investigation and, in certain cases, costly immunohistological and genetic techniques. Computational approaches enabling morphological-based decision making are necessary for bridging the existing gaps. Histopathological images can be accurately classified using deep learning approaches, however data on NHL subtyping is limited. However, there … …Journal of Computer Science, Vol. 20, Issue 5 · 28 Feb 2024 · 4,545 accessesView PDFCite