Firas Abedi¹, Hayder M. A. Ghanimi², Abeer D. Algarni³, Naglaa F. Soliman^3,*, Walid El-Shafai^4,5, Ali Hashim Abbas⁶, Zahraa H. Kareem⁷, Hussein Muhi Hariz⁸, Ahmed Alkhayyat⁹

Computer Systems Science and Engineering, Vol.47, No.3, pp. 2791-2814, 2023, DOI:10.32604/csse.2023.038762

Abstract Data mining plays a crucial role in extracting meaningful knowledge from large-scale data repositories, such as data warehouses and databases. Association rule mining, a fundamental process in data mining, involves discovering correlations, patterns, and causal structures within datasets. In the healthcare domain, association rules offer valuable opportunities for building knowledge bases, enabling intelligent diagnoses, and extracting invaluable information rapidly. This paper presents a novel approach called the Machine Learning based Association Rule Mining and Classification for Healthcare Data Management System (MLARMC-HDMS). The MLARMC-HDMS technique integrates classification and association rule mining (ARM) processes. Initially, the chimp optimization algorithm-based feature selection (COAFS)… More >

Monerah M. Alawadh^*, Ahmed M. Barnawi

Journal on Big Data, Vol.4, No.1, pp. 1-25, 2022, DOI:10.32604/jbd.2022.021744

Abstract The market trends rapidly changed over the last two decades. The primary reason is the newly created opportunities and the increased number of competitors competing to grasp market share using business analysis techniques. Market Basket Analysis has a tangible effect in facilitating current change in the market. Market Basket Analysis is one of the famous fields that deal with Big Data and Data Mining applications. MBA initially uses Association Rule Learning (ARL) as a mean for realization. ARL has a beneficial effect in providing a plenty benefit in analyzing the market data and understanding customers’ behavior. An important motive of… More >

Guwei Li¹, Zhou Li^1,*, Cong Zheng¹, Zhengyuan Li²

Journal of New Media, Vol.4, No.1, pp. 41-50, 2022, DOI:10.32604/jnm.2022.027883

Abstract Aiming at the safety problems of toxic, flammable and explosive chemicals used in middle school chemical experiments, such as human poisoning, skin corrosion, fire or explosion caused by improper experimental operation, a virtual simulation method of chemical experiments based on unity is proposed. Due to the need to analyze and compare the data in chemical experiments, summarize the experimental characteristics and data relevance. Therefore, based on the Apriori algorithm, this method deeply excavates the data obtained in the chemical experiment, uses Maya to model the experimental environment, uses unity to design the interactive functions in the experimental process, and uses… More >

Maojian Chen^1,2,3, Xiong Luo^1,2,3,*, Yueqin Zhu⁴, Yan Li^1,2,3, Wenbing Zhao⁵, Jinsong Wu⁶

Intelligent Automation & Soft Computing, Vol.26, No.5, pp. 973-987, 2020, DOI:10.32604/iasc.2020.010129

Abstract The past decade has witnessed the rapid advancements of geological data analysis techniques, which facilitates the development of modern agricultural systems. However, there remains some technical challenges that should be addressed to fully exploit the potential of those geological big data, while gathering massive amounts of data in this application field. Generally, a good representation of correlation in the geological big data is critical to making full use of multi-source geological data, while discovering the relationship in data and mining mineral prediction information. Then, in this article, a scheme is proposed towards intelligent mining of association rules for geological big… More >

Xinbao Wang^*, Dawu Huang, Xuemin Zhao

Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 755-763, 2020, DOI:10.32604/iasc.2020.010110

Abstract In order to improve the judgment decision ability of the sports training effect, a design method of the sports training decision support system based on the improved association rule, the Apriori algorithm is proposed, and a phase space model of the sports training decision support data association rule distribution is constructed. The association rule mining method is used to support the data mining model of sports training, and the decision judgment of the sports training effect is carried out in the mixed cloud computing environment. The fuzzy information fusion and the data structure feature reorganization method is adopted, and the… More >

Lini Cai^∗

Computer Systems Science and Engineering, Vol.35, No.3, pp. 183-189, 2020, DOI:10.32604/csse.2020.35.183

Abstract In this paper, we use modern education concept and satisfaction theory to study the construction of a system used to evaluate Japanese teaching quality based on a satisfaction model. We use a cloud computing platform to mine the rules of Japanese teaching quality satisfaction by using an improved Apriori algorithm to explore the impact of measurement indicators of teaching objectives, processes and results on overall satisfaction with Japanese teaching practices, so as to improve Japanese teaching in the future. Scientific decision-making, improvement of teaching practices, transformation and innovation of students’ learning methods provide data reference and theoretical support. More >

Babar Shazad¹, Hikmat Ullah khan², Zahoor-ur-Rehman¹, Muhammad Farooq², Ahsan Mahmood¹, Irfan Mehmood^3,*, Seungmin Rho³, Yunyoung Nam^4,*

Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 87-98, 2020, DOI:10.31209/2019.100000130

Abstract The social media has become an integral part of our daily life. The social web users interact and thus influence each other influence in many aspects. Blogging is one of the most important features of the social web. The bloggers share their views, opinions and ideas in the form of blog posts. The influential bloggers are the leading bloggers who influence the other bloggers in their online communities. The relevant literature presents several studies related to identification of top influential bloggers in last decade. The research domain of finding the top influential bloggers mainly focuses on feature centric models. This… More >