利用图形数据库计算缅甸人口普查数据中查找人之间联系的时间复杂度

Kay Thi Yar, Khin Mar Lar Tun
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引用次数: 0

摘要

人与人之间的关系搜索对于获取相关信息、家谱关系和个人历史变得越来越重要。本文提出了从个人信息中挖掘人际关系的框架,分为三个部分。第一部分重点介绍了将人员表示为节点,将其属性表示为属性,从而在Graph数据库中存储数据的存储结构。在这个系统中,人员节点之间没有预定义的关系或边界。第二部分侧重于搜索分离的人员节点之间的关系。提出了一种图形数据库搜索算法——人员关系搜索算法。最后提出了一种基于匹配域(或)属性搜索结果的演绎推理算法,该算法使用预定义的序言规则定义两个人之间的关系。例如,如果匹配域是亲属,则关系可能是血缘关系,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,则关系可以在同一组织中工作,等等。计算了两种算法的时间复杂度,以评估每个案例研究的运行时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Calculating time complexity for searching connections among persons from Myanmar census data using graph database
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.
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