Research on parallelization of Apriori algorithm in association rule mining

Wang, Huanbin; Gao, Yangjun

doi:10.1016/j.procs.2021.02.109

Cited by 33 publications

(14 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Peng [19] defines "curriculum and integration of educational resources platform" as follows: a curriculum and integration of educational resources platform is a platform for improving the quality of education and teaching by using information technology to organically integrate various resources, technologies, and environments that help and facilitate students' learning with the curriculum content they are learning [19]. Wang and Gao [20] published the idea of optimizing students' English reading through multimedia network teaching resources, and they wanted to use concrete image resources to make the abstract information in reading concrete and thus facilitate the learning of English reading for the majority of students [20].…”

Section: Multimedia-assisted English Integration Of Educationalmentioning

confidence: 99%

Integration and Recommendation of Multimedia Network-Assisted English Instructional Resources Based on Association Rules Mining

Liu¹

2022

Mobile Information Systems

View full text Add to dashboard Cite

The integration of multimedia teaching refers to a novel teaching mode that combines multimedia, information resources, and information methods with content and teaching process in the teaching process with the guidance of contemporary educational ideas and organically unifies them on a spatial and temporal platform, so as to better accomplish the teaching tasks. However, with the deepening of network teaching and school connotation construction, various resources such as media materials, courseware, network courses, and teaching cases generated by education and teaching, as well as academic works, papers, patents, project results, and lectures of experts and professors gathered by scientific research, are increasing. In this situation, how to integrate teaching resources and courses to provide students with an independent learning platform and an information-based learning environment has become an urgent issue. For this problem, data mining has shown a strong vitality, and data mining can find out the potential connection between datasets. Association rule mining is the most researched and widely used data mining method. In this paper, we propose a multimedia network-assisted English integration of educational resources method based on association rule algorithm to give full play to the role of “multimedia technology” and realize the integration of traditional English teaching and information network culture, so as to achieve the purpose of optimizing English teaching. The experimental results show that with the increase of data volume, the average testing time of Apriori is reduced by 56.49 s compared with MapReduce, so the advantage of Apriori algorithm is more obvious. Therefore, this research can effectively provide students with rich and colorful personalized resources, realize high-performance interactive learning, and help students cultivate their independent learning ability as well as their lifelong learning habits.

show abstract

Section: Multimedia-assisted English Integration Of Educationalmentioning

confidence: 99%

Integration and Recommendation of Multimedia Network-Assisted English Instructional Resources Based on Association Rules Mining

Liu¹

2022

Mobile Information Systems

View full text Add to dashboard Cite

show abstract

“…Xie proposed a dynamic hash pruning algorithm that not only eliminates unsatisfied candidate sets in each iteration, but also eliminates records in the database that do not contain frequent sets, which can reduce the size of the database and the time required to scan the time required to scan the database [22]. Wang and Gao partitioned the transaction records based on 1-itemsets and calculated the support of candidate 1-itemsets by selecting the item with the lowest support in the 1-itemset, the candidate element set, and then dividing the support of the candidate element set of the transaction records that traverse the element based on the previous analysis of the 1-item frequent set [23]. Silva et al proposed a partitioning algorithm that logically divides the horizontal database into several non-repeating modules and then reads each module with the IDs of the records in the database as a set of elements, and then intersects these ID element sets to produce a local frequent element set [24].…”

Section: Algorithm Of Apriorimentioning

confidence: 99%

Algorithm of Apriori-Based Rural Tourism Driving Factors and Its System Optimization

Xiao

2022

Mobile Information Systems

View full text Add to dashboard Cite

Rural tourism, as a vital component of tourism, is critical to the development of rural economies, farmers’ income, rural civilization, new rural construction, and urban-rural interaction. Simultaneously, as the size and complexity of data sets grow larger, how to improve the efficiency of association rule algorithms for mining large data sets has become a hot topic in association rule mining. Rural tourism development that is cultural and creative not only contributes to rural revitalization, but also to the preservation and inheritance of rural culture. The Apriori algorithm is the most widely used and influential algorithm for mining Boolean association rules, and the majority of current algorithms are extensions of the Apriori algorithm. Demand, supply, marketing, and support forces of rural tourism, which are the core driving force of rural tourism development, are formed by the basic needs of each subsystem of rural tourism. One of the main methods is to promote the sustainable and healthy development of rural tourism in accordance with the nature, characteristics, and laws of rural tourism destination construction, in order to create a dynamic system for long-term development and establish a rural tourism development dynamic system. The study of rural tourism driving factors and their system optimization is proposed in this paper. The main tourism dynamic system is adopted by the association rule algorithm of Apriori, the driving factors of rural tourism development are analyzed in the paper, and the system optimization method is proposed, all based on the Apriori algorithm. In terms of support, the Apriori algorithm is 0.436 higher than the CD algorithm and 0.568 higher than the SVM algorithm, and the Apriori algorithm can greatly reduce database size and improve record reading speed. As a result, the findings of this paper can be used to improve the spatial layout of rural tourism and to develop urban-rural tourism.

show abstract

“…The question is considering a company listed as a product of research and takes annual and quarterly data from 2003 to 2020 as a data center and runs 32 financial indicators [16][17] . Classify data samples from financial indicators and eliminate abnormal values.…”

Section: Fig 1 Apriori Algorithm Flowmentioning

confidence: 99%

Risk Identification Method of Enterprise AccountingInformation Fraud Based on Weighted Association Rule Algorithm

Li¹,

Yao²

2022

Proceedings of the 2022 International Conference on Computer Science, Information Engineering and Digital Economy (CSIEDE 2022)

View full text Add to dashboard Cite

In order to reduce the financial risks existing in enterprises, this paper studies the risk identification of enterprise accounting information fraud with weighted key algorithm. Based on the study of fuzzy association rules, this study analyzes the financial risks of enterprises, puts forward an analysis model of enterprise financial risks based on fuzzy association rules mining algorithm, and makes a qualitative analysis of enterprise financial crises, so as to predict enterprise financial risks and provide reference for enterprises to avoid risks. Comparing the correlation algorithm with the linear regression model, the result shows that the prediction error rate of the linear regression model is higher than that of the correlation algorithm model. Class I misjudgment rate is 40% higher, class II misjudgment rate is flat, overall misjudgment rate is 20% higher, and accuracy linear regression is 20% lower than correlation algorithm. It can be seen that the misjudgment rate of the correlation algorithm model is low, the prediction accuracy is high, and the discrimination and prediction ability of the linear regression model is poor, which proves the effectiveness of the application of the correlation algorithm in this paper.

show abstract

Research on parallelization of Apriori algorithm in association rule mining

Cited by 33 publications

References 7 publications

Integration and Recommendation of Multimedia Network-Assisted English Instructional Resources Based on Association Rules Mining

Integration and Recommendation of Multimedia Network-Assisted English Instructional Resources Based on Association Rules Mining

Algorithm of Apriori-Based Rural Tourism Driving Factors and Its System Optimization

Risk Identification Method of Enterprise AccountingInformation Fraud Based on Weighted Association Rule Algorithm

Contact Info

Product

Resources

About