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Human-Computer Interaction and Knowledge Discovery (HCI-KDD): What Is the Benefit of Bringing Those Two Fields to Work Together?

机译:人机互动和知识发现(HCI-KDD):带来这两个领域共同努力的好处是什么?

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A major challenge in our networked world is the increasing amount of data, which require efficient and user-friendly solutions. A timely example is the biomedical domain: the trend towards personalized medicine has resulted in a sheer mass of the generated (-omics) data. In the life sciences domain, most data models are characterized by complexity, which makes manual analysis very time-consuming and frequently practically impossible. Computational methods may help; however, we must acknowledge that the problem-solving knowledge is located in the human mind and - not in machines. A strategic aim to find solutions for data intensive problems could lay in the combination of two areas, which bring ideal pre-conditions: Human-Computer Interaction (HCI) and Knowledge Discovery (KDD). HCI deals with questions of human perception, cognition, intelligence, decision-making and interactive techniques of visualization, so it centers mainly on supervised methods. KDD deals mainly with questions of machine intelligence and data mining, in particular with the development of scalable algorithms for finding previously unknown relationships in data, thus centers on automatic computational methods. A proverb attributed perhaps incorrectly to Albert Einstein illustrates this perfectly: "Computers are incredibly fast, accurate, but stupid. Humans are incredibly slow, inaccurate, but brilliant. Together they may be powerful beyond imagination". Consequently, a novel approach is to combine HCI & KDD in order to enhance human intelligence by computational intelligence.
机译:我们网络世界的主要挑战是日益增加的数据,需要有效和用户友好的解决方案。及时的例子是生物医学领域:个性化医学的趋势导致了生成的( - MOCICS)数据的纯粹质量。在生命科学域中,大多数数据模型的特征在于复杂性,这使得手动分析非常耗时,频繁地是不可能的。计算方法可能有所帮助;但是,我们必须承认解决问题的知识位于人类思想中,而不是在机器中。找到数据密集问题解决方案的战略目标可能置于两个区域的组合,这带来了理想的预先条件:人机互动(HCI)和知识发现(KDD)。 HCI涉及人类感知,认知,智力,决策和可视化互动技术的问题,因此它主要针对监督方法。 KDD主要涉及机器智能和数据挖掘的问题,特别是开发可扩展算法,用于查找以前在数据中的未知关系,因此在自动计算方法上的中心。普及归因于Albert Einstein的谚语是完美的:“计算机非常快,准确,但愚蠢。人类非常慢,不准确,但辉煌。他们可以在想象力之外强大。因此,一种新的方法是将HCI&KDD组合,以通过计算智能来增强人类智能。

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