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5th International Conference on Bioinformatics Research and Applications (ICBRA)

作者： Lim, Sangwu Yoon, Taeseon Hankuk Acad Foreign Studies 15 Wiryedong Ro Seongnam Si Gyeonggi Do South Korea Hankuk Acad Foreign Studies 50Oedae Ro 54Beon Gil Yongin Gyeonggi Do South Korea

ISBN: (纸本)9781450366113

Human metapneumovirus has persistently been the leading causative agent of acute respiratory infections in young children and the elderly worldwide. The respiratory tract illness caused by HMPV yields fatal levels of morbidity and mortality rate in young children under five and the immunocompromised. To study the genetic structure of HMPV, this paper conducts a genomic analysis of the nine genes (N, P, M, F, M2-1, M2-2, SH, G, and L) of human metapneumovirus subtype A1, A2, B1, and B2. Through multiple sequence alignments, decision tree, apriori algorithm, and phylogenetic reconstruction, this paper investigates the genome-wise discrepancy and the protein-wise discrepancy between different HMPV strains. The results of the experiment indicate that the four HMPV subtypes show high similarity while displaying distinct attributes. The role of glycoprotein (G) and small hydrophobic protein (SH) are found to display the most variance among the four subtypes. The apriori algorithm shows that amino acid serine and lysine are the most frequent among the four subtypes. Under apriori algorithm 19 window, it has been found that the four subtypes display some degree of similarity in terms of their frequencies of the amino acid lysine(K). On the other hand, two clades of HMPV seem to split in terms of their frequencies of the amino acid serine(S). Hence, the role of glycoprotein and small hydrophobic protein and the contribution of amino acids serine and lysine to the nine polypeptides are suggested as a future research.

关键词： apriori algorithm Bioinformatics Decision tree Human metapneumovirus Phylogenetic reconstruction

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apriori algorithm on Web Logs for Mining Frequent Link

Apriori Algorithm on Web Logs for Mining Frequent Link

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IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing (INCOS)

作者： Sathya, M. Devi, P. Isakki Ayya Nadar Janaki Ammal Coll Dept Comp Sci Sivakasi Tamil Nadu India Ayya Nadar Janaki Ammal Coll Dept Comp Applicat Sivakasi Tamil Nadu India

ISBN: (纸本)9781509047789

Web mining is a combination of data mining and World Wide Web. It consists of three types namely web structure mining, web content mining and web usage mining. Web Usage Mining is one of the parts of web mining and extracts the web users' behavior from web log file. This paper consists of three phases. The first one is data preprocessing phase, which is the most important one because it makes the data with good quality. This can be done by data cleaning, user identification, and session identification. The next one is pattern discovery phase;in this the users' navigational pattern and rules are extracted by using apriori algorithm. Final one is pattern analysis phase, which is used to analyze and visualize the rules. The aim of this paper is to identify the frequent link from web log data by using the apriori algorithm.

关键词： Web mining Web usage mining Data cleaning User Identification Session Identification apriori algorithm

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Benefits transfer research of public companies shareholders based on apriori algorithm

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JOURNAL OF DISCRETE MATHEMATICAL SCIENCES & CRYPTOGRAPHY 2017年第4期20卷 861-872页

作者： Shen, Yongxi Quanzhou Vocat Coll Econ & Business Dept Accounting & Auditing Quanzhou 362000 Fujian Peoples R China

In this paper, the interests of shareholders conveying governance as the theme, the perspective of the interests of the transport path focus on the interests of transport path forming motivation mechanism. Association rules and transport governance model is based on theoretical and empirical study results. The interest of the path is based on the path set innovative ideas, the interests and institutional innovations governance new delivery mode. Mainly, to the concept of innovation as the guide, strengthen the system of governance, data governance and cultural governance, promote scientific management. A path of innovation support and improve the interests of the transport path of internal control system, which improved the capital market system. Shareholders' tunneling mass of raw data, combined with the lack of research among multi-source, heterogeneous and complex property features. Data mining technology as well as both the decision to introduce the association rule mining interests conveying path association patterns mining necessity.

关键词： MV models Association rules apriori algorithm Credit risk of infection

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Research on apriori algorithm Optimization of Cloud Computing and Big Data in Software Engineering

Research on Apriori Algorithm Optimization of Cloud Computin...

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2018 5th International Conference on Electrical & Electronics Engineering and Computer Science(ICEEECS 2018)

作者： Wang Rui Yunnan Engineering Vocational College

With the continuous expansion of data information, it is more and more difficult to extract effective data information from data analysis. Traditional data analysis algorithms can no longer meet the needs of big data analysis. The rise of Cloud computing provides a new solution to this problem. This paper studies the Cloud computing technology and data mining and analyses the apriori algorithm. Based on its limitations, it proposes an optimization scheme and introduces the MapReduce model in Cloud computing to achieve parallelization. A MapReduce-based frequent item set mining method is proposed to improve the efficiency of the algorithm and reduce the overhead required for algorithm execution.

关键词： Cloud computing data mining apriori algorithm MapReduce frequent item sets

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apriori-Based algorithm for Dubai Road Accident Analysis

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Procedia Computer Science 2019年 163卷 218-227页

作者： Maya John Hadil Shaiba Sree Buddha College of Engineering Pathanamthitta Kerala India Princess Nourah bint Abdulrahman University Riyadh Kingdom of Saudi Arabia

With the increased usage of private vehicles, the number of road accidents have shown an increasing trend. In this study, we applied data mining techniques to analyze the traffic accident data pertaining to Dubai for the year 2017. The data for analysis is obtained from the official open data portal of United Arab Emirates. apriori algorithm has been employed to mine frequent itemsets. Studies have been conducted to identify the major causes and trends associated with road accidents. Further experiments have been carried out to analyze the major causes of accidents during peak accident times and weekdays/weekends. It has been observed that majority of accidents involve vehicle hitting another vehicle due to inadequate space between vehicles. Another finding was that youth were involved in the majority of accidents. The results show that accidents’ peak time was during late night and that the majority of drivers were found to be intoxicated. Studies conducted show that during weekend’s peak accident time, majority of the drivers were intoxicated, while during weekday’s peak accident time, the maximum number of accidents occurred due to lack of enough space between vehicles. On the basis of the results obtained, certain recommendations which aid in reducing the accident rate have been put forward.

关键词： apriori algorithm Dubai Accident

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Improved apriori algorithm for Mining Association Rules

Improved Apriori Algorithm for Mining Association Rules

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2018 International Conference on Modeling, Simulation and Analysis(ICMSA 2018)

作者： Yu-gang DAI Xiang ZHANG Tao XU Lin YE Ya-jing MA Northwest Minzu University Key Laboratory of Chinese Language and Information Technology of Ministry of Education

apriori algorithm as a classic algorithm in data mining,it has a good performance in a small number of transactions in the database which has been widely used by people,but the algorithm has two inherent flaws,affect the efficiency of apriori algorithm mining information in large *** at the Bottleneck Problem Restricting the Efficiency of apriori algorithm,in this paper,two inherent flaws of apriori algorithm are improved,in order to improve apriori algorithm in large database mining *** algorithm reduces the number of connections and the number of database scan to shorten the database scan *** results show,the optimized apriori algorithm has some improvements in operation efficiency.

关键词： apriori algorithm Association rules Data mining Frequent itemsets

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Analysis of HSV-1 and HSV-2 that Cause Herpes Simplex with apriori algorithm, Decision Tree, and Support Vector Machine 19

Analysis of HSV-1 and HSV-2 that Cause Herpes Simplex with A...

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19th International Conference on Advanced Communication Technology (ICACT)

作者： Lee, Juhyun Jung, Yeojin Shin, Seungho Yoon, Taeseon HAFS Int Course Yongin Gyeonggi Do South Korea Korea Univ Dept Comp Educ Seoul South Korea Ansan Univ Ansan South Korea Hankuk Acad Foreign Studies Yongin Gyeonggi Do South Korea

ISBN: (纸本)9788996865094

The Herpes Simplex is a common fluid-intermitted disease that is common among not only adults but also children. Several symptoms include blisters and sores forming on infection sites that are mainly located in oral and genital body parts. The two main types of viral infection, commonly referred to as HSV-1 and HSV-2, are both part of the same Herpes Simplex Virus group (HSV), but they exhibit different characteristics in the main target of infection and the location of the infection sites. Normal cases of HSV-1 cause oral lesions and has less dangers of cross-generation infection when the female is pregnant, whereas HSV-2 cause genital lesions and usually is co-infected with human immunodeficiency virus type 1(HIV-1). Currently, no specific permanent vaccination is available for this disease and since it is chronic and can be transmitted as long as symptoms are present, the development of vaccination is significant at this stage. In order to provide further possibilities for vaccination development, we analyzed the genomes of HSV-1 and HSV-2 by using apriori algorithm, Decision tree algorithm, and Support Vector Machine. Thus, we extracted results that showed the similarity and differences of the two genomes, mainly focusing on the prominent distribution of amino acids in each of the 3 categories we have chosen - dividing the genomes up in to 13, 17, and 19 windows. Through this, we have showed further potential in developing effective vaccination more specific to each type of Herpes Simplex.

关键词： Herpes Simplex HSV-1(herpes simplex virus type 1) HSV-2(herpes simplex virus type 2) apriori algorithm Decision Tree SVM(Support Vector Machine)

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Mining Frequent Quality Factors of Software System Using apriori algorithm 1st

Mining Frequent Quality Factors of Software System Using Apr...

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1st International Conference on Data Engineering and Communication Technology (ICDECT)

作者： Agarwal, Jyoti Dubey, Sanjay Kumar Tiwari, Rajdev Amity Univ Noida Uttar Pradesh India Noida Inst Engn & Technol Greater Noida India

ISBN: (纸本)9789811016783;9789811016776

Success or failure of any software system mainly depends on its quality. Quality plays a key role for determining the acceptability and adoptability of the software system among the users. Quality is the composite characteristic that depends on its different factors. The researchers have been focusing on different quality factors as per their research work requirement and various quality factors have been proposed by them in different quality models to assess the software quality. These models show that there are differences in the perception of the researchers regarding the important quality factors. Ample research work has been done in the field of software quality but till date no work has been done to prove as which quality factors are frequently used and have high importance. This paper is an attempt to find out the major key factors of the software quality. Various quality models have been considered for this purpose and accordingly data set is prepared. apriori algorithm is used to generate the frequent quality factors. Experiment is performed in Java programming language. The aim of this research paper is to provide proper focus on the frequently used quality factors, which facilitate to improve the quality of software system. These quality factors will be useful to assess the quality of software system in a prudent manner.

关键词： Quality Models Factors Software system apriori algorithm

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Axle Fault Prognostics of Electric Multiple Units based on Improved apriori algorithm 29

Axle Fault Prognostics of Electric Multiple Units based on I...

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第29届中国控制与决策会议

作者： Li Li Tianyun Shi Weijiao Zhang China Academy of Railway Science Lan zhou jiao tong University

ISBN: (纸本)9781509046584

To effectively reduce the occurrence rate of axle faults of electric multiple units(EMUs), in this study, classical apriori algorithm is improved based on Apache Hadoop big data and applied to prediction studies of axle faults of EMUs. First, for deficiencies of the classical apriori algorithm, the improved apriori algorithm that is constrained by business experience is proposed under the Map Reduce framework. Second, based on the improved apriori algorithm put forward in this paper, in-depth data mining of information of one of the railway bureaus, such as EMU status, fault warning, and maintenance history, is conducted. The axle fault of the EMUs is then predicted through the obtained association rules. Finally, experimental results indicate that the proposed algorithm reaches an accuracy of 67% and its operation efficiency in experimental environments is improved by 50% when compared with the operation efficiency of the classical apriori algorithm.

关键词： Intelligent Transportation Fault Prognostics apriori algorithm Data Mining Big Data

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Decision Support Systems in Health Care - Velocity of apriori algorithm

Decision Support Systems in Health Care - Velocity of Aprior...

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European Federation for Medical Informatics Special Topic Conference (EFMI STC)

作者： Somek, Mario Hercigonja-Szekeres, Mira Univ Appl Hlth Sci Zagreb Croatia

ISBN: (纸本)9781614998242;9781614998235

The amount of stored data in health information systems can reach tera- and petabytes and application of specific algorithms in the field of data mining makes finding useful information suitable for making quality business decisions. A frequently used method for determining the rules of the relationship between attributes is the Association rule by applying apriori algorithm. Lack of basic apriori algorithm is derived from the slow work due to multiple scanned data sets. By examining the speed of generating the basic rules in relation to the improved apriori algorithm by using software RapidMiner confirmed that the time required to generate rules for Improved algorithm is shorter, the rules are quickly generated particularly for large data sets, which is an advantage for making decisions.

关键词： Decision support generate rules apriori algorithm Health care

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