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Towards Information Discovery On Large Scale Data: state-of-the-art

机译:对大规模数据的信息发现:最先进的

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In current age of time Knowledge Discovery in big data is on high demand and challenging process in new era of data intensive digital world. As we all know that data is being created by web, social media, and health care, Agriculture, financial, marketing, automotive industries, geo-information and other source at very large scale. Also this data proliferation is continuously increased exponentially day by day. Our aim is to find the better way to discover useful information from big data & Knowledge Discovery in Database (KDD) Processes by survey, study about the various proposed KDD framework by different researcher and its analysis with existing system. This paper represents the survey of various KDD methods applied, starts from beginning to Big Data, to extract useful information. This paper could be as root of research in the field of knowledgeable information discovery from large scale data.
机译:目前,大数据中的时间知识发现是在数据密集型数字世界的新时代的高需求和具有挑战性的过程。众所周知,数据正在由网络,社交媒体和医疗保健,农业,金融,营销,汽车行业,地理信息和其他来源创建。此数据增殖也在一天中持续增加。我们的目标是通过调查找到数据库(KDD)流程中的大数据和知识发现发现有用信息的方法,研究不同的研究人员的各种提议的KDD框架及现有系统的分析。本文代表了对应用的各种KDD方法的调查,从开始到大数据开始,以提取有用的信息。本文可以从大规模数据中发现知识渊博信息领域的研究。

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