Computer Engineering and Applications ›› 2017, Vol. 53 ›› Issue (24): 15-22.DOI: 10.3778/j.issn.1002-8331.1710-0233

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Co-location-based site selection using ontologies

BAO Xuguang, WANG Lizhen, CHEN Hongmei   

  1. Department of Computer Science and Engineering, School of Information Science and Engineering, Yunnan University, Kunming 650091, China
  • Online:2017-12-15 Published:2018-01-09



  1. 云南大学 信息学院 计算机科学与工程系,昆明 650091

Abstract: Site selection is one of the most crucial decisions made by any business. The existing approaches for site selection(commonly used by economists) are subjective, not scalable. Spatial co-location patterns represent the subsets of spatial features whose instances are frequently located together in geographic space. Thus, a novel method for site selection based on co-locations is proposed using the “symbiotic” characteristics among spatial features in co-locations. This method uses ontologies to classify the input data effectively, and then performs a co-location mining on the certain POI given by the user based on ontologies, the result co-location patterns are then used to conduct the method to give the final site recommendation in a certain location specified by the user, meanwhile, several strategies are performed in data pre-processing in order to improve the effectiveness of the proposed method. To assess the effectiveness of the presented method, it is evaluated on a real data (collected from Points of Interests in Beijing). Evaluation results show that the proposed method has high accuracy ratio, which means high reliability in site selection.

Key words: spatial data mining, co-location pattern, ontology, site selection

摘要: 选址问题是任何一个商业机构都要面临的重大决策问题之一,它受多种因素制约,比如社会经济学、地质学、生态学以及决策者的特定需求等。现有的选址方法(通常被经济学家采用)大多利用主观评价,可扩展性差。空间co-location模式挖掘是空间数据挖掘的一个重要研究方向。一个频繁co-location模式是一组空间特征的子集,它们的实例在空间中频繁关联。利用co-location模式的这种特征间“共存”关系,提出了一种基于co-location模式的地址选择算法,该算法基于本体描述空间数据的分类信息,并在本体的指导下对用户感兴趣的兴趣点(Point of Interest)进行关键co-location模式挖掘,同时针对实际情况对数据进行了预处理以增加算法的有效性。在真实数据集(北京市的兴趣点数据)上的评估实验显示该算法具有较高的准确率,选择的地址具有高可靠性。

关键词: 空间模式挖掘, co-location模式, 本体, 地址选择