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检索条件"主题词=Apriori algorithm"

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Research and Improvement of apriori algorithm 6

Research and Improvement of Apriori Algorithm

引用

6th International Conference on Information Science and Technology (ICIST)

作者： Du, Jiaoling Zhang, Xiangli Zhang, Hongmei Chen, Lei Guilin Univ Elect Technol Guangxi Coll & Univ Key Lab Cloud Comp & Complex Guilin Peoples R China

ISBN: (纸本)9781509012244

apriori algorithm is a classical association rule mining algorithm, but it has problems about frequently scanning database and generating a large number of candidate sets. To solve these problems, an improved DC_apriori algorithm was proposed, which restructured the storage structure of the database, improved connection of frequent item sets, the generation of k-frequent item sets is only need to join the 1 frequent item sets with k-1-frequent item sets, greatly reduced the number of connections and it can directly get frequent item sets by only one pruning operation, effectively avoid the unnecessary invalid candidate sets, and greatly reduce the number of scanning the database and improve the efficiency of frequent item sets generation. It has proved by experiments that. the DC_apriori algorithm is obviously superior to the apriori algorithm and the MC_apriori algorithm based on the matrix, whether in small support degree or in the intensive database with large numbers of transactions and items, the running time of DC_apriori to get the same result is significantly less than the apriori algorithm and MC_apriori algorithm based on the matrix.

关键词： Association rule mining database apriori algorithm Candidate sets Frequent item sets

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apriori-BM algorithm for Mining Association Rules based on Bit Set Matrix

Apriori-BM Algorithm for Mining Association Rules based on B...

引用

IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference

作者： Yulei Huang Qing Lin Yan Li Intelligent Science and Information Engineering College Xi'an Peihua University Xi'an China

Finding association rules is one of the most popular problems in the field of data mining. apriori is a well-known algorithm for association rule mining. It uses candidate generation and test method to find the bitmap that satisfy the minimum support threshold, but the process repeatedly scans the database and produces the plenty of candidates. A new optimization algorithm based on bit set Matrix was proposed. It just need scan the database twice to generate the bit set matrix structure needed for the algorithm. During the mining process, the infrequent itemsets were deleted in time to reduce the scanning range of the algorithm, and bit operation was used to speed up the subset detection. Experimental results show that the algorithm runs faster than apriori algorithm.

关键词： Association rule apriori algorithm Bit set computing Bit set matrix

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Comparison of episodes of mosquito borne disease: Dengue, Yellow Fever, West Nile, and Filariasis with Decision tree, apriori algorithm 18

Comparison of episodes of mosquito borne disease: Dengue, Ye...

引用

18th International Conference on Advanced Communication Technology (ICACT)

作者： Song, Seung Hye Choi, Yijeong Yoon, Taeseon Hankuk Acad Foreign Studies Nat Sci Wangsanri Yongin South Korea Korea Univ Comp Sci & Engn Anamdong Seoul South Korea

ISBN: (纸本)9788996865063

This study focuses on the mosquito borne diseases in chiding dengue-1, dengue-4, yellow fever, west nile virus infection, and filariasis. These are the diseases that are typically shown in the African continent and Eastern Asia, which are the places that suffer from poverty the most. Vaccines for some of the diseases have already been mule but the ones who inhabit in those areas do not have the ability to afford it. The research will use 3, 5, 7 windows of decision tree and apriori algorithm. By finding the similarities between the amino acid sequences between these viruses the study to find the curing for all diseases will be in progress. Emerging filariviruses: the spread and resurgence of Japanese encephalitis, West Nile and dengue viruses

关键词： Dengue-1 Dengue-4 Yello Fever West Nile Virus Filariasis Dicision Tree apriori algorithm

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Analysis and Comparison of Genomes of HIV-1 and HIV-2 Using apriori algorithm, Decision Tree, and Support Vector Machine 12th

Analysis and Comparison of Genomes of HIV-1 and HIV-2 Using ...

引用

12th International Conference on Intelligent Computing (ICIC)

作者： Roh, Yihyun Yoon, Seokhyun Lee, Min Young Jang, Seongpil Yoon, Taeseon Hankuk Acad Foreign Studies Yongin South Korea Hankuk Acad Foreign Studies Dept Sci Yongin South Korea

ISBN: (纸本)9783319422916;9783319422909

AIDS is caused by HIV, which can be divided into two strains: HIV-1 and HIV-2. Whereas HIV-1 is distributed around the world and is the major cause of global infections, HIV-2 is less infectious and transmissible and is therefore generally confined to West Africa. Thus this research aims to account for their difference by analyzing genome sequences of HIV-1 and HIV-2 using some methods: apriori algorithm, Decision tree, and Support Vector Machine. apriori demonstrates that HIV-1 has lysine, arginine, and serine as its typical amino acids, while HIV-2 has glycine, lysine, leucine, and arginine. Decision tree determines the significant positions of amino acids that can distinguish the two viruses: pos5 in 9 window, pos13 in 13 window, and pos16 in 19 window. SVM indicates that two viruses are seemingly similar but indeed different. The collective results provide a biologically verifiable background for making effective vaccines for HIV, especially for HIV-2.

关键词： HIV-1 HIV-2 Amino acids Bioinformatics Data mining apriori algorithm Decision tree Support vector machine (SVM)

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IMPLEMENTATION OF ASSOCIATION RULES WITH apriori algorithm FOR INCREASING THE QUALITY OF PROMOTION 4

IMPLEMENTATION OF ASSOCIATION RULES WITH APRIORI ALGORITHM F...

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4th International Conference on Cyber and IT Service Management

作者： Zulfikar, Wildan Budiawan Wahana, Agung Uriawan, Wisnu Lukman, Nur Sunan Gunung Djati Bandung State Islamic Univ Dept Informat Jl AH Nasut 105 Bandung West Java Indonesia

ISBN: (纸本)9781467384414

XMART is a retail company that has sold more than 5,500 products. The company intends to increase sales of products with a promotion. XMART has a history of sales up to more than 10,000,000 records. The data can then be processed with the technique used association rules by applying a priori algorithm to obtain the value of the support and confidence of every association rules. The association rules adapted to the sales potential for each store location store has a sales characteristics are manifold. The result is a combination of varied products and in accordance with the level of sales of the store. Association rules that have formed the benchmark to promote the product. In addition, the association rules that have been established to serve as a reference to determine the layout of the products in the store.

关键词： Association Rules apriori algorithm Promotion

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Transformer Defect Correlation Analysis Based on apriori algorithm 5

Transformer Defect Correlation Analysis Based on Apriori Alg...

引用

IEEE International Conference on High Voltage Engineering and Application (ICHVE)

作者： Chen, Yufeng Du, Xiuming Zhou, Liwei Shandong Elect Power Co Shandong Elect Power Res Inst Jinan Shandong Peoples R China Chongqing Univ Sch Elect Engn State Key Lab Power Transmiss Equipment & Syst Se Chongqing Peoples R China

ISBN: (纸本)9781509004966

The association rule from data mining technology was applied into transformer defect analysis so that the frequent pattern, the dependency and the causality between classification and decision attributes could be found based on data of defects. As a result, correlation properties among grid fault elements were seized macroscopically. In this paper which focused on the frequent item mining algorithm research for transformer defect correlation analysis, the definitions related to the association rule were introduced. Specific to weaknesses of traditional apriori algorithm, an efficient analogous frequent item set mining algorithm was presented. With regard to the instance, association rule analysis was carried out for data of transformer defect in Shandong. Relevant results indicated that diverse attribute items were undoubtedly associated with each other to different degrees;in addition, the correlation obtained was adopted to perform operational maintenance for auxiliary equipment and parts, etc. that are vulnerable to defects.

关键词： transformer defect correlation analysis data mining apriori algorithm

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I2apriori: An Improved apriori algorithm based on Infrequent Count

I2Apriori: An Improved Apriori Algorithm based on Infrequent...

引用

International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT)

作者： Singh, Shyam Kumar Kumar, Preetham Manipal Inst Technol Informat & Commun Technol Manipal Karnataka India

ISBN: (纸本)9781467399395

In this paper, the proposed method reduces CPU computation time by reducing transaction scan. The Concept infrequent count is based on minimum threshold support and 2-way searching to reduce execution time during scanning of transaction is introduced in proposed method. There exist several data mining algorithms for finding association rules but one of the candidate generation algorithms named apriori algorithm is considered for the proposed work.

关键词： Association Rules apriori algorithm Infrequent Count Two-way searching

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Constraint Data Mining using apriori algorithm with AND Operation 1

Constraint Data Mining using Apriori Algorithm with AND Oper...

引用

IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology (RTEICT)

作者： Shankar, Shashi Kant Kaur, Amritpal Lovely Profess Univ Dept Comp Sci & Engn Phagwara Punjab India

ISBN: (纸本)9781509007745

Data mining is one of the most important steps in knowledge discovery. apriori algorithm is the most used one in this process. The major drawback with apriori algorithm is of time and space. It generates numerous uninteresting itemsets which lead to generate various rules which are of completely of no use. The two factors considered for association rules generation are Minimum Support Threshold and Minimum Confidence Threshold. However, constraint mining reduces these two limitations of apriori algorithm to a considerable extent. This paper uses constraint mining and AND operation between MST and MCT to prune itemsets generated in each iteration. The overall performance has been increased and simulated in this paper through various figures from simulation result.

关键词： data mining apriori algorithm constrained data mining constraint data mining MST MCT

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Research on Audit Log Association Rule Mining Based on Improved apriori algorithm

Research on Audit Log Association Rule Mining Based on Impro...

引用

IEEE International Conference on Big Data Analysis (ICBDA)

作者： Cheng, Maocai Xu, Kaiyong Gong, Xuerong Inst Zhengzhou Informat Sci & Technol Zhengzhou 450004 Peoples R China

ISBN: (纸本)9781467395915

Aimed at solving the problem of low-level intelligence and low utilization of audit logs of the security audit system, a secure audit system based on association rule mining is proposed in this paper. The system is able to take full advantage of the existing audit logs, establish the behavior pattern database of users and the system with data mining technique, and discover abnormal situation in a timely manner, which improves the security of computer system. We propose an improved E-apriori algorithm which narrows the scanning range of the transactions, lowers the time complexity, and refines the operating efficiency. Experiment results on the Weka platform indicate that our proposed E-apriori algorithm clearly outperforms the traditional apriori algorithm, especially in the large sparse datasets.

关键词： security audit systemaudit log data mining association rule mining apriori algorithm

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Agricultural major Courses recommendation using apriori algorithm applied in China Open University system 9

Agricultural major Courses recommendation using Apriori Algo...

引用

9th International Symposium on Computational Intelligence and Design (ISCID)

作者： Liu, Fang Zhang, Shaogang Ge, Junyi Lu, Feng Zou, Jun Open Univ China Res Inst Open & Distance Educ Beijing Peoples R China Open Univ China Sch Econ & Management Beijing Peoples R China Open Univ China Sch Educ Beijing Peoples R China

ISBN: (纸本)9781509035588

In open and distance education field, making use of data mining technologies to understand students' practical needs and usage habits about professional courses, which will greatly enhance students learning. China Open University system is Chinese largest scale organization engaging in open and distance education, and it has taken Chinese education ministry's a rural education project, called "one college student in one village". The system should teach nationwide students agricultural professional courses through network. This paper proposes a professional courses recommendation scheme for agricultural major students, including "student course selection rules producing module" and "student course selection rules searching and matching module". In the overall scheme's core functional design, apriori algorithm is improved to find local and global frequent course-selection sets, and local and global strong association rules about student professional courses selection, thus to recommend professional courses more intelligently according to student practical needs. Proposed scheme is applied in China Open University system's Animal Husbandry and Veterinary major, a part of "one college student in one village" project, and process of providing course recommendation service by using proposed scheme is illustrated.

关键词： Course recommendation apriori algorithm Open University Rural education

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