Based on petrophysical data mining application of K-means clustering analysis, it elaborated the practical significance of application asso- ciation with big data technology in well logging field, which also provided a
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2016/12/23· Research and Citation Analysis of Data Mining Technology Based on Bayes Algorithm Mingyang Liu 1, Ming Qu 2 & Bin Zhao 3 Mobile Networks and Applications volume 22, pages 418 – 426 (2017)Cite this article 525 Accesses ...
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Data mining technology is through all the data onto a certain range of data collection, data classification and data collection, and then determine whether there is a potential relationship between the law and data, there are three main areas: The first is prepare data ; the second is to find the law of
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1 Data Mining Technology for the Evaluation of Web-based Teaching and Learning Systems Claus Pahl, Dave Donnellan Dublin City University School of Computer Applications Dublin 9, Ireland [cpahl|ddonnell]@computing.dcu.ie ...
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Data mining projects for engineers researchers and enthusiasts. Get the widest list of data mining based project titles as per your needs. These systems have been developed to help in research and development on information mining ...
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network based on data mining technology Yanli Bai Abstract Data mining technology is a very common computer technology, which has been widely used in many fields because of its superior performance. The method of talent ...
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2020/01/29· Data mining programs analyze relationships and patterns in data based on what users request. For example, a company can use data mining software to create classes of information. To illustrate ...
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Several data-mining models have been embedded in the clinical environment to improve decision making and patient safety. Consequently, it is crucial to survey the principal data-mining strategies currently used in clinical decision making and to determine the disadvantages and advantages of using these strategies in data mining in clinical .
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Revista de la Facultad de Ingeniería U.C.V., Vol. 32, N 5, pp. 338-346, 2017 338 Analysis of Financial Data Anomaly Based on Data Mining Technology Qin Xu* School of Economics & Management, Chengdu Textile College, China
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Data mining is a process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. [1] Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal to extract information (with intelligent methods) from a data set and transform the .
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2011/11/01· Our main interest was to identify research goals, diabetes types, data sets, data-mining methods, data-mining software and technologies, and outcomes. Results The applications of data-mining techniques in the selected articles were useful for extracting valuable knowledge and generating new hypothesis for further scientific .
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Data Mining Technology for the Evaluation of Web-based Teaching and Learning Systems. In M. Driscoll & T. Reeves (Eds.), Proceedings of E-Learn 2002--World Conference on E-Learning in Corporate, Government, Healthcare, and .
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A Cloudbased Energy Data Mining Information Agent This paper aims to develop the cloudbased energy data mining information agent system ontodma as based on the wias cloud environment and big data analysis technology which ...
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2019/09/14· WIT120 data mining technology based on internet of things Qingyuan Zhou 1,2,3, Zongming Zhang 4,5 & Yuancong Wang 6 Health Care Management Science (2019)Cite this article 347 Accesses 1 Altmetric Metrics details ...
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2018/11/01· Data Mining Based On Perturbation Technique Information Technology Essay Abstract To the success of today's data mining techniques preserving personal and sensitive information is critical.
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Data mining is a process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal to extract information (with intelligent methods) from a data set and transform the information .
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Data mining and predictive models are at the heart of successful information and product search, automated merchandizing, smart personalization, dynamic pricing, social network analysis, genetics, proteomics, and many other ...
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A Cloudbased Energy Data Mining Information Agent This paper aims to develop the cloudbased energy data mining information agent system ontodma as based on the wias cloud environment and big data analysis technology which ...
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2016/12/23· Research and Citation Analysis of Data Mining Technology Based on Bayes Algorithm Mingyang Liu 1, Ming Qu 2 & Bin Zhao 3 Mobile Networks and Applications volume 22, pages 418 – 426 (2017)Cite this article 525 Accesses ...
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Data Mining Technology Based on Association Rule in Students' Grades Analysis (Taking the Computer Science and Technology Major of HZNU as an Example) Jingwei Diao, Yani Wang, Yiming Liu and Huansong Yang on the ...
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Distributed data mining (DDM) techniques have become necessary for large and multi-scenario datasets requiring resources, which are heterogeneous and distributed. In this paper, we focused on distributed data mining based in grid. We have discussed and analyzed a new framework based on grid environments to execute new distributed data mining .
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2020/08/13· Data Mining technique has to be chosen based on the type of business and the type of problem your business faces. A generalized approach has to be used to improve the accuracy and cost-effectiveness of using data mining techniques. There are basically seven main Data Mining techniques which are discussed in this article.
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2004/10/01· Data mining is a process which finds useful patterns from large amount of data. The paper discusses few of the data mining The paper discusses few of the data mining techniques, algorithms and some of the organizations which have adapted data mining technology to improve their businesses and
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2017/05/04· Research uses Weka big data mining technology platform to analyze the data.The association rules miningmethods of discrete sample data by Weka technology,using SimpleKMeans clustering algorithm for clustering analysisof thesimulated sample data mining, common features of each type of data and the difference data between differentclusters from where, for a variety of data .
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Abstract - The current data mining technology has the mismatch problem of mining keywords and used words, which leads to low mining precision and low efficiency. In this paper, a new data mining algorithm based on association rule algorithm is proposed.
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[8] Niugai Fang, Jing Wang, Qingyu Sun, A New Data Mining Algorithm based on Improved Neural Network, 2009 Asia-Pacific Conference on Information Processing, pp: 320-323. [9] Dr Shuxiang Xu, Prof Ming Zhang, Data Mining-An Adaptive Neural Network Model for Financial Analysis, Proceedings of the Third International Conference on Information Technology .
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Abstract: With the continuous expansion of computer simulation scale, the demand for data mining algorithm is also more and more big. The difficulties in computer data mining technology are focused on algorithm development. [4] Rui Wang, Rui Li, Haiyun Xiong etc. Implementation of visual Apriori algorithm based on association rules [J]. ...
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2012/12/11· Within a data mining exercise, the ideal approach is to use the MapReduce phase of the data mining as part of your data preparation exercise. For example, if you are building a data mining exercise for association or clustering, the best first stage is to build a suitable statistic model that you can use to identify and extract the necessary .
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2020/07/01· 3.2. Data mining technology One of the tasks when applying data mining techniques to analyze data is to discover patterns from the data. Generally, it can be divided into the descriptiveness of the mining task and the predictability
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The traditional land-use statistics based on administrative districts can not represent the spatial differences of land-use composition entirely. By introducing spatial hierarchy and non-spatial hierarchy the Statistical Information Grid-Based method is extended then it can manage and analyze land-use statistics in virtue of a kind of multi-grid data .
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