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From data mining to wisdom mining
Journal of Information Science ( IF 1.8 ) Pub Date : 2021-07-12 , DOI: 10.1177/01655515211030872
Salma Khan 1 , Muhammad Shaheen 1
Affiliation  

The knowledge gained from data mining is highly dependent on the experience of an expert for further analysis to increase effectiveness and wise decision-making. This mined knowledge requires actionability enhancement before it can be applied to real-world problems. The literature highlights the reasons that emerged the need to incorporate human wisdom in decision-making for complex problems. To solve this problem, a domain called ‘Wisdom Mining’ is recommended, proposing a set of algorithms parallel to the algorithms proposed by the data mining. In wisdom mining, a process to extract wisdom needs to be defined with less influence from an expert. This review proposed improvements to data mining techniques and their applications in the real world and emphasised the need to seek ways to harness wisdom from data. This study covers the diverse definitions and different perspectives of wisdom within philosophy, psychology, management and computer science. This comprehensive literature review served as a foundation for constructing a wise decision framework that aided in identifying the wisdom factors like context, utility, location and time. The inclusion of these wisdom factors in existing data mining algorithms makes the transition from data mining to wisdom mining possible. This research includes the relationship between these two mining process that facilitated further elucidation of the wisdom mining process. Potential research trends in the domain are also seen as a potential endeavour to improve the analysis and use of data.



中文翻译:

从数据挖掘到智慧挖掘

从数据挖掘中获得的知识高度依赖于专家的经验,以便进一步分析以提高有效性和明智的决策。这种挖掘出的知识需要增强可操作性,然后才能应用于现实世界的问题。文献强调了需要将人类智慧纳入复杂问题决策的原因。为了解决这个问题,推荐了一个名为“智慧挖掘”的领域,提出了一组与数据挖掘提出的算法并行的算法。在智慧挖掘中,需要在专家的影响较小的情况下定义提取智慧的过程。该评论提出了对数据挖掘技术及其在现实世界中的应用的改进,并强调需要寻求从数据中挖掘智慧的方法。这项研究涵盖了哲学、心理学、管理学和计算机科学中智慧的不同定义和不同观点。这份全面的文献综述为构建明智的决策框架奠定了基础,该框架有助于确定背景、效用、位置和时间等智慧因素。将这些智慧因素包含在现有的数据挖掘算法中,使得从数据挖掘到智慧挖掘的转变成为可能。这项研究包括这两个挖掘过程之间的关系,有助于进一步阐明智慧挖掘过程。该领域的潜在研究趋势也被视为改进数据分析和使用的潜在努力。这份全面的文献综述为构建明智的决策框架奠定了基础,该框架有助于确定背景、效用、位置和时间等智慧因素。将这些智慧因素包含在现有的数据挖掘算法中,使得从数据挖掘到智慧挖掘的转变成为可能。这项研究包括这两个挖掘过程之间的关系,有助于进一步阐明智慧挖掘过程。该领域的潜在研究趋势也被视为改进数据分析和使用的潜在努力。这份全面的文献综述为构建明智的决策框架奠定了基础,该框架有助于确定背景、效用、位置和时间等智慧因素。将这些智慧因素包含在现有的数据挖掘算法中,使得从数据挖掘到智慧挖掘的转变成为可能。这项研究包括这两个挖掘过程之间的关系,有助于进一步阐明智慧挖掘过程。该领域的潜在研究趋势也被视为改进数据分析和使用的潜在努力。将这些智慧因素包含在现有的数据挖掘算法中,使得从数据挖掘到智慧挖掘的转变成为可能。这项研究包括这两个挖掘过程之间的关系,有助于进一步阐明智慧挖掘过程。该领域的潜在研究趋势也被视为改进数据分析和使用的潜在努力。将这些智慧因素包含在现有的数据挖掘算法中,使得从数据挖掘到智慧挖掘的转变成为可能。这项研究包括这两个挖掘过程之间的关系,有助于进一步阐明智慧挖掘过程。该领域的潜在研究趋势也被视为改进数据分析和使用的潜在努力。

更新日期:2021-07-12
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