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International Journal of Advanced Research in Big Data Management System最新文献

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Identifying Social Media Influencers using Graph Based Analytics 使用基于图形的分析识别社交媒体影响者
International Journal of Advanced Research in Big Data Management System Pub Date : 2020-05-30 DOI: 10.21742/ijarbms.2020.4.1.04
Pankti Joshi, Sabah Mohammed
{"title":"Identifying Social Media Influencers using Graph Based Analytics","authors":"Pankti Joshi, Sabah Mohammed","doi":"10.21742/ijarbms.2020.4.1.04","DOIUrl":"https://doi.org/10.21742/ijarbms.2020.4.1.04","url":null,"abstract":"Social network analysis has been an essential topic with broad content sharing from social media. Defining the directed links in social media determine the flow of information and indicates the user’s influence. Due to the enormous data and unstructured nature of sharing information, there are several challenges caused while handling data. Graph Analytics proves to be an essential tool for addressing problems such as building networks from unstructured data, inferring information from the system, and analyzing the community structure of a network. The proposed approach aims to determine the influencers on Twitter data, based on the follower’s links as well as the retweet links. Several graph-based algorithms are implemented on the data collected to find the influencer as well as conversation communities in the network of twitter users.","PeriodicalId":377126,"journal":{"name":"International Journal of Advanced Research in Big Data Management System","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124097518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Improved K-Means Clustering Algorithm Based on Dynamic Clustering 基于动态聚类的改进 K-Means 聚类算法
International Journal of Advanced Research in Big Data Management System Pub Date : 2020-05-30 DOI: 10.21742/ijarbms.2020.4.1.02
Li-Guo Zheng
{"title":"Improved K-Means Clustering Algorithm Based on Dynamic Clustering","authors":"Li-Guo Zheng","doi":"10.21742/ijarbms.2020.4.1.02","DOIUrl":"https://doi.org/10.21742/ijarbms.2020.4.1.02","url":null,"abstract":"Cluster analysis can not only find potential and valuable structured information in the data set, but also provide pre-processing functions for other data mining algorithms, and then can refine the processing results to improve the accuracy of the algorithm. Therefore, cluster analysis has become one of the hot research topics in the field of data mining. K-means algorithm, as a clustering algorithm based on the partitioning idea, can compare the differences between the data set classes and classes. We can use the K-means algorithm to mine the clustering results and further discover the potentially valuable knowledge in the data set. Help people make more accurate decisions. This paper summarizes and analyzes the traditional K-means algorithm, summarizes the improvement direction of the K-means algorithm, fully considers the dynamic change of information in the K-means clustering process, and reduces the standard setting value for the termination condition of the algorithm to reduce The number of iterations of the algorithm reduces the learning time; the redundant information generated by the dynamic change of information is deleted to reduce the interference in the dynamic clustering process, so that the algorithm achieves a more accurate and efficient clustering effect. Experimental results show that when the amount of data is large, compared with the traditional K-means algorithm, the improved K-means algorithm has a greater improvement in accuracy and execution efficiency. 1","PeriodicalId":377126,"journal":{"name":"International Journal of Advanced Research in Big Data Management System","volume":"5 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141202044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Data Analytics through BlockChain Technologies 通过区块链技术进行数据分析
International Journal of Advanced Research in Big Data Management System Pub Date : 2020-05-30 DOI: 10.21742/ijarbms.2020.4.1.03
C. Sekhar, N. Rao
{"title":"Data Analytics through BlockChain Technologies","authors":"C. Sekhar, N. Rao","doi":"10.21742/ijarbms.2020.4.1.03","DOIUrl":"https://doi.org/10.21742/ijarbms.2020.4.1.03","url":null,"abstract":"Huge Information is a term for a considerable amount, not predictable, emergent data collections among abundant, self-reliant sources. Created in different fields extending from monetary and business exercises to open organization, plays a significant role to take any decision. Blockchain is a dispersed database framework that goes about as an \"open record\" to store and oversee exchanges. Each trace in the DB(Database) is known as a square and contain points of interest, for example, the exchange timestamp and besides a connection to the past square. Makes it unthinkable for everybody to change data about the records thoughtfully. Furthermore, since the way that a similar exchange can record over the various, dispersed database structure, the innovation is secure by the plan. This paper provides the fundamentals of big data and how we can use the blockchain technology.","PeriodicalId":377126,"journal":{"name":"International Journal of Advanced Research in Big Data Management System","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131834392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A survey on Machine Learning Classifiers and Big data for Accurate and Reliable Heart Disease Pre-diagnosis 机器学习分类器与大数据在心脏病准确可靠预诊断中的应用研究
International Journal of Advanced Research in Big Data Management System Pub Date : 2019-11-30 DOI: 10.21742/ijarbms.2019.3.2.04
Srikanth Meda
{"title":"A survey on Machine Learning Classifiers and Big data for Accurate and Reliable Heart Disease Pre-diagnosis","authors":"Srikanth Meda","doi":"10.21742/ijarbms.2019.3.2.04","DOIUrl":"https://doi.org/10.21742/ijarbms.2019.3.2.04","url":null,"abstract":"Since a decade, emergence of interdisciplinary computer technologies changed the pace of medical diagnosis systems by insisting up-to-date intelligence and supervision. These intellectual systems predict the future health problems by processing the current health information of patients, which helps in prevention of diseases rather than cure. Although the medical diagnosis systems are adequate intelligent in disease diagnosis, but they are still suffering in pre-diagnosis of diseases due to the complexity in processing of huge medical datasets. Recently introduced Data Mining techniques with Big Data processing environment expanded the horizons of medical diagnosis systems to process the high velocity medical data sets to diagnose the occurrence of diseases early. Today’s medical diagnosis systems, which are utilizing different data mining techniques like Decision Trees (DT), Support Vector Machines (SVM), Naïve Bayes (NB), Fuzzy Logics and K-Nearest Neighbor (KNN), are suffering from uncertainty, imprecision and complexity in processing. In this paper we are proposing a cross reference methodology to improvise the reliability and precision of diagnostic results and utilizing big data tools to diminish the complexity in processing huge sets of medical data. Most popular data mining techniques, which are participating in medical data processing with high accuracy are selected and cross referenced by our proposed framework to overcome uncertainty and imprecision. In order to process the high velocity medical datasets with several data mining techniques, this frame work outsources the data processing business to Apache Hadoop environment. Experiments on Cleveland medical dataset proved that the proposed cross reference methodology framework recorded high precision, recall and accuracy in results than its counterparts.","PeriodicalId":377126,"journal":{"name":"International Journal of Advanced Research in Big Data Management System","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134051642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Implementation of Integrated Authentication Service using Blockchain and One Time QR Code for Access Control in U-city Environment 基于区块链和一次性二维码的U-city环境下门禁集成认证服务的实现
International Journal of Advanced Research in Big Data Management System Pub Date : 2019-11-30 DOI: 10.21742/ijarbms.2019.3.2.03
J. Kim
{"title":"Implementation of Integrated Authentication Service using Blockchain and One Time QR Code for Access Control in U-city Environment","authors":"J. Kim","doi":"10.21742/ijarbms.2019.3.2.03","DOIUrl":"https://doi.org/10.21742/ijarbms.2019.3.2.03","url":null,"abstract":"This paper proposes an integrated user authentication system that can be used for access control in U-city environment. The proposed integrated authentication system issues an EID capable of acting as an electronic ID to a user based on a smartphone, and verifies and verifies the access to a building or a specific space using the issued EID. Unlike the user authentication using a smart card, it can be used in on / off-line environment because authentication service is provided in web service environment. Based on the issued EID, one-time authentication information is used in the authentication process in the form of One Time QRcode to provide a secure authentication process from security breaches such as retransmission attacks. In addition, the security and security of the network and computing environment have been improved because the user's authentication information is issued and verified in a blockchain-based decentralized system rather than the existing centralized system.","PeriodicalId":377126,"journal":{"name":"International Journal of Advanced Research in Big Data Management System","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116197203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
A Survey on Several Challenges with Their Solutions in Big Data Along with Applications 大数据解决方案及其应用中的几个挑战调查
International Journal of Advanced Research in Big Data Management System Pub Date : 2019-05-30 DOI: 10.21742/ijarbms.2019.3.1.01
{"title":"A Survey on Several Challenges with Their Solutions in Big Data Along with Applications","authors":"","doi":"10.21742/ijarbms.2019.3.1.01","DOIUrl":"https://doi.org/10.21742/ijarbms.2019.3.1.01","url":null,"abstract":"","PeriodicalId":377126,"journal":{"name":"International Journal of Advanced Research in Big Data Management System","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123084874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Artificial Intelligence Methodologies for Supervised Learning 监督学习的人工智能方法
International Journal of Advanced Research in Big Data Management System Pub Date : 2019-05-30 DOI: 10.21742/ijarbms.2019.3.1.03
{"title":"Artificial Intelligence Methodologies for Supervised Learning","authors":"","doi":"10.21742/ijarbms.2019.3.1.03","DOIUrl":"https://doi.org/10.21742/ijarbms.2019.3.1.03","url":null,"abstract":"","PeriodicalId":377126,"journal":{"name":"International Journal of Advanced Research in Big Data Management System","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124965762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Apparel Recommendation System Using Descriptive Textual Similarity of Products 基于产品描述文本相似度的服装推荐系统
International Journal of Advanced Research in Big Data Management System Pub Date : 2019-05-30 DOI: 10.21742/ijarbms.2019.3.1.04
{"title":"Apparel Recommendation System Using Descriptive Textual Similarity of Products","authors":"","doi":"10.21742/ijarbms.2019.3.1.04","DOIUrl":"https://doi.org/10.21742/ijarbms.2019.3.1.04","url":null,"abstract":"","PeriodicalId":377126,"journal":{"name":"International Journal of Advanced Research in Big Data Management System","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122520712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Random Forest Regression for Estimating the Requirements of Online Report Analysis 随机森林回归估计在线报表分析需求
International Journal of Advanced Research in Big Data Management System Pub Date : 2019-05-30 DOI: 10.21742/ijarbms.2019.3.1.02
{"title":"Random Forest Regression for Estimating the Requirements of Online Report Analysis","authors":"","doi":"10.21742/ijarbms.2019.3.1.02","DOIUrl":"https://doi.org/10.21742/ijarbms.2019.3.1.02","url":null,"abstract":"","PeriodicalId":377126,"journal":{"name":"International Journal of Advanced Research in Big Data Management System","volume":"38 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125736121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Study on Frame Work of H2O For Data Science 面向数据科学的H2O框架研究
International Journal of Advanced Research in Big Data Management System Pub Date : 2018-11-30 DOI: 10.21742/ijarbms.2018.2.2.01
{"title":"A Study on Frame Work of H2O For Data Science","authors":"","doi":"10.21742/ijarbms.2018.2.2.01","DOIUrl":"https://doi.org/10.21742/ijarbms.2018.2.2.01","url":null,"abstract":"","PeriodicalId":377126,"journal":{"name":"International Journal of Advanced Research in Big Data Management System","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122340131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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