大数据挖掘外文翻译文献.docx

文献信息： 文献标题：A Study of Data Mining with Big Data（大数据挖掘研究） 国外作者：VH Shastri，V Sreeprada 文献出处：《International Journal of Emerging Trends and Technology in Computer Science》,2016,38(2):99-103 字数统计：英文2291单词，12196字符；中文3868汉字 外文文献：　 A Study of Data Mining with Big Data Abstract Data has become an important part of every economy, industry, organization, business, function and individual. Big Data is a term used to identify large data sets typically whose size is larger than the typical data base. Big data introduces unique computational and statistical challenges. Big Data are at present expanding in most of the domains of engineering and science. Data mining helps to extract useful data from the huge data sets due to its volume, variability and velocity. This article presents a HACE theorem that characterizes the features of the Big Data revolution, and proposes a Big Data processing model, from the data mining perspective. Keywords: Big Data, Data Mining, HACE theorem, structured and unstructured. I.Introduction Big Data refers to enormous amount of structured data and unstructured data that overflow the organization. If this data is properly used, it can lead to meaningful information. Big data includes a large number of data which requires a lot of processing in real time. It provides a room to discover new values, to understand in-depth knowledge from hidden values and provide a space to manage the data effectively. A database is an organized collection of logically related data which can be easily managed, updated and accessed. Data mining is a process discovering interesting knowledge such as associations, patterns, changes, anomalies and significant structures from large amount of data stored in the databases or other repositories. Big Data includes 3 V’s as its characteristics. They are volume, velocity and variety. Volume means the amount of data generated every second. The data is in state of rest. It is also known for its scale characteristics. Velocity is the sp