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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:人机交互和知识发现(HCI-KDD):将这两个领域协同工作有什么好处?

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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:我们网络世界中的主要挑战是数据量的不断增长,这就需要高效且用户友好的解决方案。生物医学领域是一个及时的例子:个性化医学的趋势导致生成的大量数据(组学)。在生命科学领域,大多数数据模型都具有复杂性,这使得手工分析非常耗时,而且实际上几乎是不可能的。计算方法可能会有所帮助;但是,我们必须承认解决问题的知识位于人的大脑中,而不是机器中。找到解决数据密集型问题的解决方案的战略目标可能在于两个领域的结合,这带来了理想的前提条件:人机交互(HCI)和知识发现(KDD)。 HCI处理人类感知,认知,智力,决策和可视化交互技术的问题,因此它主要集中在监督方法上。 KDD主要处理机器智能和数据挖掘的问题,特别是开发可伸缩算法以查找数据中以前未知的关系,因此着眼于自动计算方法。可能被错误地归因于爱因斯坦的谚语完美地说明了这一点:“计算机非常快,准确,但是很愚蠢。人类非常慢,不准确但很聪明。它们在一起可能强大,超出了想象。”因此,一种新颖的方法是将HCI和KDD结合起来,以通过计算智能来增强人类智能。

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