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Application of the Spatial Data Mining Methodology and Gamification for the Optimisation of Solving the Transport Issues of the 'Varsovian Mordor'

机译:空间数据挖掘方法和游戏化在解决“ Varsovian Mordor”运输问题的优化中的应用

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The objective of the paper was to develop a specialised knowledge base using data mining methods, as the basis for and expert, decision making support system, created for the needs of development of action against negative spatial phenomena, which occur within the biggest office district of the capital of Poland. After collecting representative answers to a questionnaire from responders, who are professionally involved with this area, the authors "enriched the data" with commonly accessible spatial information and analysed the resulting dataset using artificial, regression and classification neural networks, CART decision trees and created fuzzy inference systems. Inference rules, developed with the use of the knowledge base and a limited amount of accessible information allow to specify highly probable types of social problems important for particular employees of this district. Using data mining techniques, the authors transformed collected data into information and knowledge, diagnosing main infrastructural and spatial problems in "Varsovian Mordor". Generalisation of inference rules, developed as a result of knowledge acquisition allowed the authors to propose unique, social gamification techniques, precisely dedicated for particular groups of inhabitants and employees of "the Mordor".
机译:本文的目的是使用数据挖掘方法开发一个专门的知识库,以此为基础并建立专家决策支持系统,以开发针对消极空间现象的行动,而消极空间现象发生在该州最大的办公区域内。波兰的首都。在收集了来自该领域专业人士的问卷调查表的代表性答案后,作者使用通常可访问的空间信息“丰富了数据”,并使用人工,回归和分类神经网络,CART决策树分析了所得数据集,并创建了模糊模型。推理系统。通过使用知识库和有限的可访问信息而开发的推理规则,可以指定对于该地区特定员工而言非常重要的高度可能的社会问题类型。使用数据挖掘技术,作者将收集的数据转换为信息和知识,从而诊断了“ Varsovian Mordor”中的主要基础设施和空间问题。由于知识获取而产生的推理规则的一般化,使作者能够提出独特的社交游戏化技术,专门针对“魔多”的特定居民和雇员群体。

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