Enhancing the Performance in Generating Association Rules using Singleton Apriori

Mani, K.; Akila, R.

doi:10.5815/ijitcs.2017.01.07

Cited by 8 publications

(4 citation statements)

References 7 publications

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“…With the rapid development of information technology, the trend of campus informatization is gradually taking shape, and China has entered the era of standardized education management informatization construction to some extent [ 9 ]. Student management informatization plays an important role in the modernization of school management.…”

Section: The Basic Concepts Of Data Mining and Student Management Inf...mentioning

confidence: 99%

Information Reconstruction of Student Management Work Based on Association Rules Mining

Xiang

Shuai

et al. 2022

Computational Intelligence and Neuroscience

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In recent years, as the country has paid more and more attention to the education, informatization of student management has become more and more important. This article aims to study how to reconstruct the informatization of student management which is based on association rule mining. This article mainly introduces association rule mining and student management informationization. Based on data mining, an algorithm for association rules is proposed, and the algorithm is used to mine student management informationization. From the data in the experiment, it can be seen that the efficiency of traditional student management is between 25% and 35%, whereas the efficiency of student management information based on association rules is between 64% and 72%. It can be seen that the efficiency of student management work combined with association rule mining is significantly higher than that of traditional management methods. From the data, we can see that in 2017, the development trend of colleges and universities adopting information management rose from about 5.4% to about 11%, and the development trend of colleges and universities adopting information management rose from about 7.5% to about 33% in 2018. In student management, the simplification of information can effectively improve the efficiency of student management, so the reconstruction of student management information based on association rule mining has become very important.

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Section: The Basic Concepts Of Data Mining and Student Management Inf...mentioning

confidence: 99%

Information Reconstruction of Student Management Work Based on Association Rules Mining

Xiang

Shuai

et al. 2022

Computational Intelligence and Neuroscience

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“…Validity of this model was verified by using the medical records (cases) of sleep apnea hypoventilation syndrome which was provided by the hospital. In the real world, there are usually interdependent or interrelated relationships between things, and when something is already known, the things that are related or dependent on it can be inferred, and the rules that express such related or dependent relationships between things are called association rules [8]. At present, association rules have important applications in different fields.…”

Section: Introductionmentioning

confidence: 99%

Application of Apriori Improvement Algorithm in Asthma Case Data Mining

Zheng

Pei-pei

Chen

et al. 2021

Journal of Healthcare Engineering

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In Chinese medicine, asthma cases contain a large amount of empirical data which are obtained from the clinical diagnosis of doctors throughout the year. Data correlation analysis method is among the common mechanisms which are used to mine association between the (1) prescriptions and prescribers (doctors in this case) and (2) symptoms and medications for a particular disease in the hospitals. In this paper, initially, a thorough analysis of expected performance and shortcomings of the Apriori algorithm in mining of medical case data is presented. Secondly, we propose an extended version of the traditional Apriori algorithm which is primarily based on the fast response of computer to bit-string logic operation. A comparative evaluation of the proposed and existing Apriori algorithms is presented particularly in terms of running time, mining of frequent items set and strong association rules. Both experimental and simulation results have proved that the proposed extended Apriori algorithm has outperformed existing algorithms when it is applied to asthma medication and combined symptom-medication data for the association analysis. Furthermore, the association relationship between mind asthma case data and medication is effective in the analysis of asthma case data with significant application value which is verified by the experimental data and observations.

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“…class none IF : age in {pre-presbyopic,presbyopic} ^ spectacle-prescrip in {hypermetrope} ^ astigmatism in {yes} ^ tear-prod-rate in {normal} (2) class none IF : age in {young,pre-presbyopic,presbyopic} ^ spectacle-prescrip in {myope,hypermetrope} ^ astigmatism in {no,yes} ^ tear-prod-rate in {reduced} (12) class soft IF : age in {presbyopic} ^ spectacle-prescrip in {hypermetrope} ^ astigmatism in {no} ^ tearprod-rate in {normal} (1) class soft IF : age in {young,pre-presbyopic} ^ spectacle-prescrip in {myope,hypermetrope} ^ astigmatism in {no} ^ tear-prod-rate in {normal} (4) class hard IF : age in {pre-presbyopic,presbyopic} ^ spectacle-prescrip in {myope} ^ astigmatism in {yes} ^ tear-prod-rate in {normal} (2) class none IF : age in {presbyopic} ^ spectacle-prescrip in {myope} ^ astigmatism in {no} ^ tear-prod-rate in {normal} (1) class hard IF : age in {young} ^ spectacle-prescrip in {myope,hypermetrope} ^ astigmatism in {yes} ^ tear-prod-rate in {normal} (2)…”

Section: Nnge Rulesmentioning

confidence: 99%

“…For this reason, the use of expert systems is increasing and also being used in a number of sectors of our social and technological life. In fact, in those the use of expert systems is becoming quite a significant aspect during problem solving and decision support [9][10][11][12][13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Designing a Rule Based Expert Systems for Contact Lenses Patients

Aydilek¹,

Gümüşçü²

2018

IJITCS

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Abstract-Expert systems that bring facts and valuable experiences together and make some deductions possible. Expression of relevant knowledge and experience in these structures may be in a set of rules. Learning problems are valid with expert systems. Therefore, they cannot add new rules and information automatically by themselves. Rules are created by human experts on the way and added upon the system. Classification datasets are collections of data commonly used in machine learning that contain and classify the previously obtained experiences. In this study, rules were obtained by using Part, NNge, Prism rule classifier algorithms, and a knowledge base of expert systems was systematically created to achieve enrichment. Enrichment and rule deduction process needs careful and sensitive attention. A combined methodology and study was revealed during this sensitive process. In this context, studies were conducted on five widely used datasets. It was aimed to reduce the redundant, conflicting, subsumed and circular rules in order to create a consistent and complete knowledge base. In this way, a methodology was developed to establish more powerful and richer contents of knowledge base that have higher quality.

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Enhancing the Performance in Generating Association Rules using Singleton Apriori

Cited by 8 publications

References 7 publications

Information Reconstruction of Student Management Work Based on Association Rules Mining

Information Reconstruction of Student Management Work Based on Association Rules Mining

Application of Apriori Improvement Algorithm in Asthma Case Data Mining

Designing a Rule Based Expert Systems for Contact Lenses Patients

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