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Research on parallelization of apriori algorithm in association rule mining

Procedia Computer Science 2021年 183卷 641-647页

作者： Huan-Bin Wang Yang-Jun Gao College of Equipment Management And Unmanned Aerial Vehicle Engineering of Airforce Engineering University ShanXi Xi’an 710051 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.

关键词： Association rules apriori algorithm MapReduce Parallelization

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Design and Implementation of Targeted Person Holographic Archive System based on apriori algorithm 5

Design and Implementation of Targeted Person Holographic Arc...

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5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE)

作者： Fu, Yihui Bu, Fanliang Peoples Publ Secur Univ China Sch Informat Network Secur Beijing Peoples R China

ISBN: (纸本)9781665423144

With the popularization of big data, public security organs are facing problems such as incomplete information collection, difficulty in fusion of multi-source heterogeneous data, and poor data association collected by front-end sensing devices in the management and control of targeted person. Combining the current situation and needs of public security management, this paper analyzes the targeted person's full-element information based on the apriori association rule algorithm to conduct frequent item mining on the targeted person's attribute characteristics and behavior characteristics, which can effectively identify the abnormal behavior of targeted person and obtain deduction information, and finally implements a holographic archive system based on JavaEE design that can completely describe the targeted person. Its main functions include add files, file details, advanced search, "my focus", "my supplement" and "my search". After testing, the various functions of the system are operating well, which is conducive to the public security organs in real-time grasp of targeted person's basic information, social information, behavior information and other full-element information.

关键词： Holographic archives Targeted person apriori algorithm

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Misdiagnosis Features of Ancient Clinical Records Based on apriori algorithm

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Chinese Medicine and Culture 2020年第1期3卷 50-53页

作者： Ling Yu Department of Basic Theroy of TCM Faculty of Basic MedicineShanghai University of Traditional Chinese MedicineShanghaiChina

Objective:To analyze misdiagnosis features in clinical cases of“Classified Medical Cases of Famous Physicians”and“Supplement to Classified Case Records of Celebrated Physicians.”Materials and Methods:Two hundred and five ancient misdiagnosed cases were analyzed in aspects of locations(exterior-interior type,qi-blood type and Zang‑Fu organs type)and patterns(heat-cold type and deficiency-excess type)by apriori algorithm ***:The main types of misdiagnosis in those medical casesare as follows::Zang‑Fu location misjudgment,misjudging the interior as the exterior,misjudging deficiency pattern as excess pattern,and misjudging cold pattern as heat *** them,the most outstanding type is the misjudgment of deficiency–cold pattern as excess–heat ***:(1)Accurate judgment of location and differentiation of deficiency and excess patterns are the key points in diagnosing the diseases *** confusion of true deficiency–cold and pseudo‑excess–heat pattern should be taken seriously.(2)Data mining on ancient clinical cases offers a new methodology for assisting clinical diagnosis of traditional Chinese medicine.

关键词： Ancient clinical cases apriori algorithm classified medical cases of famous physicians data mining misdiagnosis features supplement to classified case records of celebrated physicians

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An Improved apriori algorithm Research in Massive Data Environment

An Improved Apriori Algorithm Research in Massive Data Envir...

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International Conference on Cyber Security Intelligence and Analytics (CSIA)

作者： Xu, Yu Zhan, Ranzhi Tan, Gang Chen, Lu Tian, Bojin State Grid Chongqing Elect Power Co Informat Commun Branch Chongqing 400000 Peoples R China

ISBN: (纸本)9783030152352;9783030152345

Smart grid computing environment is an information platform that has lots of production data, data management, and the real-time and non real-time data. Under such massive data environment, the classic apriori algorithm of mining association rules has a significant performance bottleneck. After analyzing the apriori algorithm, the MapReduce programming model is used to realize the parallel apriori algorithm. In order to improve the mining efficiency further, auxiliary tables and attribute columns are added and parallel strategy is improved in the process of candidate itemsets generation. Simulation experiments show that the improved apriori algorithm can effectively reduce the algorithm execution time and improve the efficiency of data mining under the massive data environment.

关键词： Data mining apriori algorithm MapReduce Smart grid

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Research on Line-Loss Correlation Analysis Technology of Distribution Network Based on apriori algorithm 5

Research on Line-Loss Correlation Analysis Technology of Dis...

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5th Asia Conference on Power and Electrical Engineering (ACPEE)

作者： Huang, Wensi Chen, Jing Liu, Changqing Shi, Weiwei Lin, Chao Lyu, Xiaodong Gao, Hongjun State Grid Xintong Yili Technol Fuzhou Fujian Peoples R China Sichuan Univ Coll Elect Engn Chengdu Peoples R China

ISBN: (纸本)9781728152813

The association analysis technique and its principle represented by apriori algorithm are expounded. In this paper, the concept of "line-loss relaxation factor" is introduced to improve the traditional support and confidence, which is helpful to reduce the redundancy and improve the efficiency of the traditional algorithm. Through the analysis of the case verification, the correlation analysis technology can effectively mine the relevant factors affecting the line-loss of the distribution network, and can visually indicate the degree of influence, which is very important for proposing the corresponding impairment strategy.

关键词： distribution network line-loss correlation analysis apriori algorithm

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A Forensic Investigation of Terrorism in Nigeria: An apriori algorithm Approach

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Journal of Information Security 2021年第4期12卷 270-280页

作者： Aamo Iorliam Raymond U. Dugeri Beatrice O. Akumba Samera Otor Department of Mathematics & Computer Science BSU Makurdi Nigeria

Investigations towards studying terrorist activities have recently attracted a great amount of research interest. In this paper, we investigate the use of the apriori algorithm on the Global Terrorism Database (GTD) for forensic investigation purposes. Recently, the apriori algorithm, which could be considered a forensic tool, has been used to study terrorist activities and patterns across the world. As such, our motivation is to utilise the Apriori algorithm approach on the GTD to study terrorist activities and the areas/states in Nigeria with high frequencies of terrorist activities. We observe that the most preferred method of terrorist attacks in Nigeria is through armed assault. Again, our experiment shows that attacks in Nigeria are mostly successful. Also, we observe from our investigations that most terrorists in Nigeria are not suicidal. The main application of this work can be used by forensic experts to assist law enforcement agencies in decision making when handling terrorist attacks in Nigeria.

关键词： Forensics Terrorism Nigeria apriori algorithm

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Inferring implications in semantic maps via the apriori algorithm

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LINGUA 2020年 239卷 102808-102808页

作者： Zeng, Ni Xiao, Hong Wuhan Univ Coll Chinese Language & Literature 299 Bayi Rd Wuhan 430072 Peoples R China

Semantic maps are powerful tools for analyzing cross-language variations with implications between semantic functions to construct the relevant conceptual space. However, as existing semantic maps cannot illustrate the imbalance of implications between functions, a further discussion of inferring implications is highly demanded. The problem of inferring implications and the imbalance of implications between functions above is similar to the well-known problem of generating all significant association rules between items purchased by customers, and the apriori algorithm offers an effective solution to relieve such issue. Here, alternative schematic diagrams based on the apriori algorithm are employed to supplement semantic maps, which is justified by reproducing the same results as Cysouw obtained on person marking using his datasets. Furthermore, in our study, an implication in number from singular to plural is observed in person marking. We have solved the issue of imbalance and obtained credible implication rules between primitives in groups. We can mine practicable directed implication rules and reveal rules hard to notice before, such as active primitives between groups. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Implications Semantic maps Typology apriori algorithm

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Characteristics Predicting a High Caregiver Burden in Patients with Vascular Cognitive Impairment: Using the apriori algorithm to Delineate the Caring Scenario

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RISK MANAGEMENT AND HEALTHCARE POLICY 2021年 14卷 1335-1351页

作者： Jhang, Kai-Ming Wang, Wen-Fu Chang, Hsin-Fang Chang, Ming-Che Wu, Hsin-Hung Changhua Christian Hosp Dept Neurol Changhua Taiwan Ming Dao Univ Dept Holist Wellness Changhua Taiwan Natl Changhua Univ Educ Dept Business Adm Changhua Taiwan Changhua Christian Hosp Dept Nucl Med Changhua Taiwan Asia Univ Dept M Commerce & Multimedia Applicat Taichung Taiwan State Univ Malang Fac Educ Malang East Java Indonesia

Purpose: The aim of this study was to elucidate the factors and caring scenarios associated with a moderate to severe care burden in the caregivers of patients with vascular cognitive impairment (VCI). Patients and Methods: This cross-sectional study included 158 patients with VCI and their caregivers who were managed by the dementia collaborative care team at Changhua Christian Hospital, Taiwan. Gender, age, clinical dementia rating, walking ability, behavioral symptoms, and psychological symptoms were the variables from the patients with VCI. Age, marital status, relation to the VCI patient, education, employment status, help of key activities, type of primary care, frequency of care, ZBI (Zarit burden interview) caregiving burden, and caregiver's mood were the evaluated variables for the caregivers. The apriori algorithm was used to identify the attributes that resulted in different caregiving burdens from a comprehensive viewpoint of both VCI patients and their caregivers. Results: A total of 1193 rules were identified with 1134 rules belonging to caregivers with a mild to moderate burden and 59 rules belonging to caregivers with a moderate to severe burden. Seven general rules were created based on a summary of these 59 rules. The results showed that an employed female caregiver who was taking care of her husband alone for >= 6 days per week, and who was helping with all key activities was likely to experience a moderate to severe burden when the patient had VCI. Moreover, if the caregiver had a relatively low education level and expressed an abnormal mood during the assessment, this increased the likelihood of the caregiver having a moderate to severe burden. Conclusion: The caregiver's gender, relation to the care recipient, education level, mood status, employment status, and care loading were associated with a higher burden of care for caregivers of patients with VCI. Therefore, a dementia care team should provide personalized training for caregivers about

关键词： vascular cognitive impairment dementia caregivers caregiving burden Zarit burden interview caring scenario apriori algorithm

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Network Intrusion Detection Based on apriori-Kmeans algorithm 1

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3rd International Conference on 3D Imaging Technologies - Multidimensional Signal Processing and Deep Learning (3DIT-MSP and DL)

作者： Zhang, Yiying Wang, Delong Wu, Yannian Liu, Yiyang Zhang, Nan Li, Yingzhuo Tianjin Univ Sci Technol Coll Artificial Intelligence Tianjin 300457 Peoples R China Shenzhen Guodian Technol Commun Co Ltd Shenzhen 518000 Peoples R China

ISBN: (数字)9789811924484

ISBN: (纸本)9789811924484;9789811924477

Timely detection of network intrusion is an indispensable part of network security;therefore, how to accurately detect network intrusion is particularly important. Based on this, this paper proposes an intrusion detection model based on apriori-Kmeans algorithm to detect network intrusion, in order to ensure the normal operation of the network. Firstly, the intrusion alarm mode under the security state of feature-based NIDS is modeled, and the continuous output of NIDS intrusion alarm is filtered by apriori-Kmeans algorithm, then the similarity between points is determined by the modified distance D in apriori-Kmeans algorithm, and whether the new data point is normal or not is judged according to the similarity score, so as to reduce the false alarm rate of intrusion detection system, improve the accuracy of intrusion detection. A comparative experiment is designed, and the results show that the method proposed in this paper has high accuracy.

关键词： apriori algorithm Kmeans algorithm Intrusion detection NIDS

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Analysis and Processing of B-station Fragmentation Information Based on apriori algorithm

Analysis and Processing of B-station Fragmentation Informati...

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第17届创新与管理国际学术会议（ICIM2020）

作者： Jia Lili Wang Changyou Dianchi College Yunnan University College of Applied Mathematics Chengdu University of Information Technology

With the rapid development of the internet, the data is growing explosively. Because the information obtained by human beings is scattered, it is an important research topic to extract valuable information from fragmentary information. In this paper, by studying the characteristics of fragmented information, combining the advantages of Hadoop platform and using apriori algorithm, firstly, the collected fragmented information is processed, and the data is clustered by dividing the level sequence;secondly, the association rules are mined by apriori algorithm;finally, the popular video ranking in December 2019 is analyzed through station B, and the relationship between heat and benefit of the video are mined. Furthermore, the method of mining the potential value of fragmented information is given by using the apriori algorithm.

关键词： Fragmentation information Hadoop platform apriori algorithm Association rule mining

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