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首页> 外文会议>International Workshop on Semantic and Social Media Adaptation and Personalization >Fiscal Knowledge discovery in Municipalities of Athens and Thessaloniki via Linked Open Data
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Fiscal Knowledge discovery in Municipalities of Athens and Thessaloniki via Linked Open Data

机译：通过链接的开放数据在雅典市和塞萨洛尼基市的财政知识发现

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Data Mining and Knowledge discovery in Databases (KDD) is the process that includes data selection, pre-processing, transformation, data mining, evaluation and interpretation of the solutions from the observed results in order to discover useful knowledge from a collection of data. Semantic web and Open Linked Data can provide a higher level quality in Data Mining tasks using additional and linked information from various sources. There are many data models and different approaches that have been proposed in this area combining different aspects of Open Linked Data and Data Mining processes. OpenBudgets.eu meets this concept by modelling Open Budget data from Municipalities of Europe. This paper presents KDD process using the data model of OpenBudgets.eu in order to extract new knowledge from the budget and transaction data of Municipalities of Athens and Thessaloniki. We explored through descriptive statistics the budget phase amounts of the administrative units in Athens and Thessaloniki since 2011 and we observed that both Municipalities tried to reduce their expenditures in these years. The distributions of the expenditure amounts of services and the other descriptive measures and visualizations are provided in order to understand the structure of the expenditures of these Municipalities. Finally using cluster analysis, we built a model that categorizes what expenditure amounts an administrative unit in Athens and Thessaloniki will execute.
机译：数据库中的数据挖掘和知识发现（KDD）是一个过程，该过程包括数据选择，预处理，转换，数据挖掘，评估和根据观测结果对解决方案进行解释，以便从数据集中发现有用的知识。语义网和开放链接数据可以使用来自各种来源的附加信息和链接信息，在数据挖掘任务中提供更高级别的质量。在此领域，结合开放式链接数据和数据挖掘过程的不同方面，已经提出了许多数据模型和不同的方法。 OpenBudgets.eu通过对来自欧洲市政当局的Open Budget数据进行建模来满足此概念。本文介绍了使用OpenBudgets.eu数据模型的KDD过程，以便从雅典市和塞萨洛尼基市的预算和交易数据中提取新知识。我们通过描述性统计数据探索了自2011年以来雅典和塞萨洛尼基行政单位预算阶段的金额，我们观察到这两个市政府都试图减少这几年的支出。提供服务支出金额的分布以及其他描述性措施和可视化效果，以便了解这些市政当局的支出结构。最后，使用聚类分析，我们建立了一个模型，将雅典行政区和塞萨洛尼基将执行的支出金额分类。

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