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Calculating time complexity for searching connections among persons from Myanmar census data using graph database

机译:使用图形数据库计算从缅甸人口普查数据中搜索人际关系的时间复杂度

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Searching relationship among persons is more and more growing importance to acquire related information, genealogical relationship and personnel history. In this paper, the framework with three portions is proposed for exploring peoples' relationship from their personnel information. The first portion focuses on storage structure to store data in Graph database by representing persons as nodes and their attributes as properties. There are no predefined relationships or edges between person nodes in this system. The second part focuses on searching relationships among separated person nodes. Graph database searching algorithm called Personnel Relationship Searching Algorithm is proposed. The last portion proposes Deductive Reasoning Algorithm to define two persons' relationship based on search results of match domain (or) attributes using predefined prolog rules. For example, if the match domain is relatives, the relation may be consanguine, such as GrandFather, Eldest_Son, Youngest_Son_In_Law, Khame_Khamet, etc. If the match domain is organization (or) hobby (or) religion, the relation may work in same organization, etc. The time complexity for two proposed algorithms is calculated to evaluate the running time for each case study.
机译:搜索人与人之间的关系对于获取相关信息,家谱关系和人事历史越来越重要。本文提出了一个由三部分组成的框架,用于从人员信息中探索人们的关系。第一部分着重于通过将人表示为节点并将其属性表示为属性将数据存储在Graph数据库中的存储结构。在此系统中,人员节点之间没有预定义的关系或边缘。第二部分着重于搜索分离的人节点之间的关系。提出了一种图数据库搜索算法,称为人员关系搜索算法。最后一部分提出了演绎推理算法,以使用预定义的序言规则基于匹配域(或)属性的搜索结果来定义两个人的关系。例如,如果匹配域是亲戚,则该关系可以是近亲关系,例如祖父,Eldest_Son,Youngest_Son_In_Law,Khame_Khamet等。如果匹配域是组织(或爱好)或宗教信仰,则该关系可以在同一组织中工作,等等。计算了两种提出的算法的时间复杂度,以评估每个案例研究的运行时间。

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