Re-discovery Data Jacket’s Value by combining Cluster with Text Analysis
Re-discovery Data Jacket’s Value by combining Cluster with Text Analysis
复制标题
聚类与文本分析相结合，重新发现Data Jacket的价值
DOI：
10.1016/j.procs.2017.08.111
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Yanyuan Zeng,Yukio Ohsawa
中科院分区：
文献类型：
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作者：
岩永宇央;大澤幸生;Yanyuan Zeng,Yukio Ohsawa
自从大数据发展以来，我们一直在进行各种关于数据利用的研究，也通过数据挖掘，在以前的研究中讨论了数据价值对商业决策和规划的贡献程度的重要性。然而，数据本身的价值却没有得到足够的重视。因此，即使通过大规模步骤开发或挖掘，数据对用户也没有用处的风险很高。而且，一旦数据的价值不能充分展现，在商业方面也会造成很大的损失。本文针对数据价值评估没有固定标准的现状，构建模型对不同领域的数据进行价值评估，并对每一个数据的价值进行了相对准确的评估。为了构建这样的模型，首先重点研究了如何确定数据包的价值。数据夹的价值是否在数据市场的背景下得到充分评估？从虚拟数据市场评估出来的价值与其本身的现实有什么区别？本文重点关注其中的差距，为重新发现数据夹的价值提供了新的思路和新的方法。
Since the development of Big Data, we have been doing various researches on data utilization, also through data mining, the importance of data value in terms of degree of contribution to business decision-making and planning has been discussed in previous studies. However not enough attention has been paid to the value of the data itself. Therefore, there is a high risk that the data will not be useful to the user even if developed or mined by massive steps. Moreover, once the value of data cannot be fully demonstrated, it will also cause a great loss in terms of business. In this paper, we focus on the present condition that there is no fixed standard in the data value evaluation, the model is structured to evaluate the data from different fields, and the value of each data has been relatively accurate assessed. In order to build such a model, first of all focus on how to determine the value of Data Jackets. Are the values of the Data Jackets fully assessed in the context of the data market? What is the difference between the value evaluated from the virtual data market and the reality of itself? This paper focuses on the gap, and provides a new idea and new method for the re-discovery of the value of Data Jackets.