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APPLICATION OF IMPROVED apriori algorithm IN INNOVATION AND ENTREPRENEURSHIP ENGINEERING EDUCATION PLATFORM

SCALABLE COMPUTING-PRACTICE AND EXPERIENCE 2023年第3期24卷 609-620页

作者： Wu, Xuanyuan Xiao, Yi Liu, Anhua Hunan Commun Polytech Basic Dept Changsha 410132 Peoples R China Hunan Commun Polytech Modern Educ Technol Ctr Changsha 410132 Peoples R China Hunan Vocat Coll Sci & Technol Coll Continuing Educ Changsha 410004 Peoples R China

The implementation of innovation and entrepreneurship education is inseparable from professional education, so it is important for the rich data in the education platform to mine the connection between professional courses and between grades and courses. The study of association rule algorithm based on education data mining improves the time performance efficiency and accuracy of apriori algorithm. The study improves the time efficiencies of apriori algorithm by maintaining Map table and splitting transaction database;the accuracy is improved by using mixed criteria to measure the accuracy and filtering deformation rules based on the inference of confidence. The results of the validation of the time efficiency of the algorithm show that the running time of the improved algorithm in solving frequent itemsets is improved by about 93.86%, 92.48% and 92.76%, respectively, compared with the other three algorithms. The running time of the algorithm for generating frequent itemsets of all orders is about 91.35 ms, which is 66.13% and 83.72% better than the apriori algorithm and aprioriTid algorithm, respectively. The mining results of student examination data based on the education platform are reasonable and practical, which are of good practical significance for the innovation and entrepreneurship engineering education platform to develop training plans and improve teaching *** assumed.

关键词： Engineering education platform innovation and entrepreneurship practice association rules data mining apriori algorithm

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Using the apriori algorithm to explore caregivers’ depression by the combination of the patients with dementia and their caregivers

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Risk Management and Healthcare Policy 2021年 14卷 2953-2963页

作者： Chang, Cheng-Chen Wang, Wen-Fu Li, Yi-Ying Chen, Yu-An Chen, Yen-Jen Liao, Yi-Cheng Jhang, Kai-Ming Wu, Hsin-Hung Department of Psychiatry Changhua Christian Hospital Changhua Taiwan School of Medicine Chung Shan Medical University Taichung City Taiwan Department of Neurology Changhua Christian Hospital Changhua Taiwan Department of Holistic Wellness Ming Dao University Changhua Taiwan Department of Business Administration National Changhua University of Education Changhua Taiwan Department of M-Commerce and Multimedia Applications Asia University Taichung City Taiwan Faculty of Education State University of Malang Malang East Java Indonesia

Purpose: The purpose of this study was to identify the caring scenarios that result in severe depression in caregivers caring for dementia patients. Patients and Methods: A cross-sectional study with 1111 dementia patients and their caregivers in Taiwan from October 2015 to January 2020 was conducted. Gender, age, type of dementia, clinical dementia rating, walking ability, mood symptoms, behavioral symptoms, and psychological symptoms were the variables from the dementia patients. Age, relation to the patient, employment, type of primary care, frequency of care, mood symptoms, and the score from the Center for Epidemiologic Studies Depression Scale were the variables from the caregivers. A comprehensive viewpoint of both dementia patients and their caregivers was evaluated by the apriori algorithm to find the attributes resulting in different caregiving depressions. Results: Forty-seven rules were found with 18 rules of mild depressive symptomatology, 17 rules of moderate depressive symptomatology, and 12 rules of severe depressive symptoma-tology. A total of 7 general rules were summarized to be the severe depressive symptomatol-ogy. The results showed that an unemployed or retired caregiver with the mood symptoms such as helplessness, anger, emotional liability, or anxiety who took care of AD patients or AD patients with a moderate severity would have severe depression. Increased care frequencies (≥6 days per week) and multiple mood problems from caregivers result in severe depression. The composition of adult children, patients’ aggression, and caregivers’ helplessness as well as the combinations of male patients aged 75–84 years with the caregiver’s mood of helplessness or nervousness and hopelessness were highly associated with severe depression. Conclusion: For those caring for AD patients, severe depression was associated with the combination of different parameters to constitute each of these seven scenarios. Unlike previous studies which often evaluated on

关键词： Alzheimer’s disease apriori algorithm Behavioral and psychological symptoms of dementia Caregiver Caregiver’s mood Caring scenario Center for Epidemiologic Studies Depression Scale Depressive symptomatology Patient with dementia

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Research on parallelization of apriori algorithm in association rule mining 10

Research on parallelization of Apriori algorithm in associat...

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10th Annual International Conference of Information and Communication Technology (ICICT)

作者： Wang, Huan-Bin Gao, Yang-Jun Airforce Engn Univ Coll Equipment Management & Unmanned Aerial Vehic Xian 710051 Shanxi Peoples R China

Aiming at the performance bottleneck of traditional apriori algorithm when the data set is slightly large, this paper adopts the idea of parallelization and improves the apriori algorithm based on MapReduce model. Firstly, the local frequent itemsets on each sub node in the cluster are calculated, then all the local frequent itemsets are merged into the global candidate itemsets, and finally, the frequent itemsets that meet the conditions are filtered according to the minimum support threshold. The advantage of the improved algorithm is that it only needs to scan the transaction database twice and calculate the frequent item set in parallel, which improves the efficiency of the algorithm. (C) 2021 The Authors. Published by Elsevier B.V.

关键词： Association rules apriori algorithm MapReduce Parallelization

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Mapping of regulatory actors and processes related to cloud-based energy management environments using the apriori algorithm

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SUSTAINABLE CITIES AND SOCIETY 2022年第0期80卷 103762-103762页

作者： de Carvalho, Patricia Stefan Siluk, Julio Cezar Mairesse Schaefer, Jones Luis Fed Univ St Maria UFSM Dept Prod & Syst Santa Maria RS Brazil

Energy Cloud (EC) is the future proposal for energy management but the point is that there is no regulatory framework for EC. Therefore, knowing how the energy regulatory environment works and the relationship between actors and processes in this environment will contribute to the proposition of a new, well-structured regulatory system. The objective of this article is to identify the processes and actors which compose the regulation level of energy systems, to establish the basic relationships between these actors and processes, outlining the guidelines for the establishment and/or modification of policies, laws, and regulations related to the transition of energy management systems to the EC. The method used to achieve the objective was a systematic literature review (SLR) and the apriori algorithm. SLR identified 7 main processes and 21 secondary processes, totaling 28 regulatory processes (outlined and presented through a mental map), being established through apriori a network of dependencies between these processes with 37 direct links. 23 actors were identified that are structured in a network with 28 direct and dependent connections. The connections between processes and actors can serve as a starting point for creating a roadmap for the development of new regulations considering the implementation of EC.

关键词： Energy management Energy cloud regulation Energy regulation process apriori algorithm

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Application of Association Rule:apriori algorithm in E-Commerce

Application of Association Rule:Apriori Algorithm in E-Comme...

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Innovations in Energy management and Renewable Resources (IEMRE) Conference

作者： Das, Arijita Jana, Soumita Ganguly, Pranita Chakraborty, Nirban Inst Engn & Management Elect & Elect Kolkata W Bengal India Inst Engn & Management Elect & Elect Engn Kolkata W Bengal India

ISBN: (纸本)9781665412599

Associative classification frameworks have been effectively used to build classification frameworks. The significant strength of such strategies is that they can utilize the most exact guidelines among a comprehensive rundown of class-affiliation rules. This clarifies their great exhibition as a rule, however to the inconvenience of a costly figuring cost, acquired from affiliation rules revelation calculations. We address this issue by proposing an appropriate procedure dependent on FP-development calculation. In a shared nothing design, subsets of arrangement rules are created in equal amounts from a few information segments. A between processor correspondence is set up to settle on worldwide choices. This trade is made distinctly in the main degree of recursion, permitting each machine to thus deal with all its allotted errands autonomously. The last classifier is worked by a lion's share vote. This methodology is outlined by a definite model, and an examination of correspondence cost.

关键词： Associative Classification Definite Model FP Development apriori algorithm

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Educational Information Recommendation System for College Design Based on apriori algorithm 22

Educational Information Recommendation System for College De...

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Proceedings of the 11th International Conference on Software and Information Engineering

作者： Pan Xiao Guangzhou Academy of Fine Arts China

ISBN: (纸本)9781450397063

Educational information recommendation service is an important factor in realizing educational information sharing. In the massive educational information, users can quickly find the educational information resources they need, meet users' learning needs, and bring users a good learning experience. This paper designs an educational information recommendation system for colleges and universities. The functions provided by the system to users are mainly to facilitate the use of educational information resources. Users can choose subjects or courses to browse resources according to their own interests. This paper uses Mashup technology to integrate various educational information resources, realizes the function of educational information recommendation, and then uses the apriori algorithm to mine the characteristics of association rules, and obtains the evaluation results of educational resources according to the user's interest in educational resources.

关键词： apriori algorithm Mashup Technology Recommender System Educational Information

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Proposing Relevant Diagnosis Associated with Lung Cancer Based on Prior Diagnosis: Implementing apriori algorithm

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JOURNAL OF THORACIC ONCOLOGY 2023年第11期18卷 S735-S735页

作者： Kim, S. Y. Park, J. Cho, J. Kwak, N. Choi, S. M. Lee, J. W. Park, Y. S. Seoul Natl Univ Hosp Seoul South Korea

EP17.01-03

关键词： Lung Cancer apriori algorithm Diagnosis

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Personalized Safety Instruction Recommendation for construction workers Based on apriori algorithm 11

Personalized Safety Instruction Recommendation for construct...

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IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC)

作者： Tang, Ning Hu, Hao Xu, Feng Shanghai Jiao Tong Univ Dept Civil Engn Shanghai Peoples R China

ISBN: (纸本)9781665414906

The safety management is a focus in the construction industry, and accident causal factors are various. Many management methods are applied to improve the safety state and safety instruction is an essential part of this. However, traditional safety instruction method is always not personalized and wastes the workers more time. The authors improved the safety instruction by analysing real accident cases and the rule-based recommendation method. First, the authors analyzed 157 accident cases by Systematic Knowledge Engineering method, and and found safety accident cases mainly contain six kinds of information: accident expense, accident types, accident time, causal factors, accident location, and worker types. The causal factors are the most important part of case analysis, and they can be divided into six sub-causes according to literature review: management level, input resource to safety, construction hazards, equipment and materials, weather, qualification, physical condition, and mental state. Then apriori algorithm is used to explore the association among these accident factors to recommend more precise safety instruction for workers. Finally, expert workshops are held to evaluate the analysis results of apriori algorithm. Preliminary results show that the model can improve the traditional safety instruction by providing more precise relationship among the worker characterises and safety accidents.

关键词： Construction safety management Safety Instruction Accident cases apriori algorithm Personality

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Research on the mining of ideological and political knowledge elements in college courses based on the combination of LDA model and apriori algorithm

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APPLIED MATHEMATICS AND NONLINEAR SCIENCES 2022年第1期8卷 2345-2356页

作者： Wang, Long Shaoyang Univ Shaoyang 422099 Hunan Peoples R China

In recent years, mapping of knowledge domain and political knowledge has developed rapidly and gradually penetrated into many practical applications. The construction of an ideological and political knowledge framework for colleges has become one of the important applications. Therefore, commencing with the theory of mapping of knowledge domain, and aiming at resolving the difficulty involved in effectively extracting and analysing ideological and political knowledge, a mining method for ideological and political knowledge elements is constructed in this paper, based on LDA model and apriori algorithm. By setting a three-dimensional matrix of keywords and association rules, an algorithm for mining of ideological and political knowledge elements is proposed, where LDA model is used to acquire ideological and political subject words, and apriori algorithm is used to discover tacit ideological and political knowledge. It is helpful to solve the problem of excavation and presentation of ideological and political elements in college curriculum, serve the ideological and political construction of curriculum, which is of great significance to dredge students' learning paths and reduce learners' learning cost.

关键词： Mapping of knowledge domain LDA model apriori algorithm Ideological and political knowledge element

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Research on Analysis of Students Using Mobile Phones in Ideological and Political Classrooms by apriori algorithm of Association Rules

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Procedia Computer Science 2022年 208卷 12-17页

作者： Pan Gao

The phenomenon of college students using mobile phones in class is very common. Few students can do not use mobile phones in class, and most students have great dependence on mobile phones. Although students will use mobile phones in class according to their needs, in most cases the number of students using mobile phones will increase with the increase of classroom teaching time. In this paper, the association rule mining algorithm apriori algorithm is used to analyze the current situation of mobile phone use of full-time college students in ideological and political courses in Suzhou Vocational University. Then, the apriori algorithm based on association rules analyzes the mobile phone usage and improvement of students in ideological and political courses: cluster analysis is introduced in the preprocessing stage, and finally the algorithm is applied to the learning guidance of students' ideological and political courses, and points out the use of mobile phones by students in class. The root cause and further in-depth research on the use of mobile phone discussions in ideological and political classes.

关键词： Association rules apriori algorithm using mobile phones ideological political courses

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