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首页> 外文期刊>International journal of knowledge-based development >Strategy ontology construction and learning: Insights from Smart city strategies
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Strategy ontology construction and learning: Insights from Smart city strategies

机译:策略本体的构建与学习:智慧城市策略的见解

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Smart cities are designed to overcome problems that traditional cities face like the exponential increase of the population and related needs. Smart cities design is a relatively new research field that appeared with the concept of smart city. Unfortunately, it is a laborious and error prone task which suggests designers' expertise and adequate skills. To overcome this issue, we attempt to acquire expertise from existing strategies and projects about smart cities. For this end, we develop strategy ontology. The strategy ontology allows not only to formalise and conceptualise the strategy related concepts but also to analyse existing projects and strategies. We attempt thereafter to enrich it via automatic learning techniques. We use therefore automatic annotation of smart cities related documents. In addition to automatic annotation, we also use the ontology-based information extraction (OBIE) for ontology population and enrichment with new concepts and instances. The followed process is composed of five tasks: corpus construction, ontology population, ontology enrichment, ontology's consistency verification and ontology learning evaluation. The resulting ontology will allow sharing the gathered knowledge between people participating in the activities of smart cities design and thus learning from smart cities previous projects and strategies in order to create new ones.
机译:智慧城市旨在克服传统城市所面临的问题,例如人口的急剧增长和相关需求。智慧城市设计是随着智慧城市的概念出现的相对较新的研究领域。不幸的是,这是一项艰巨且容易出错的任务,提示了设计师的专业知识和足够的技能。为了克服这个问题,我们尝试从有关智慧城市的现有策略和项目中获取专业知识。为此,我们开发了策略本体。策略本体不仅允许将与策略相关的概念形式化和概念化,而且还可以分析现有项目和策略。此后,我们尝试通过自动学习技术来丰富它。因此,我们使用智能城市相关文档的自动注释。除了自动注释外,我们还使用基于本体的信息提取(OBIE)来进行本体填充和新概念和实例的充实。接下来的过程由五个任务组成:语料库建设,本体种群,本体丰富,本体一致性验证和本体学习评估。由此产生的本体将允许在参与智慧城市设计活动的人们之间共享收集的知识,从而从智慧城市中学习以前的项目和策略,以创建新的项目和策略。

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