基于句子数据结构的拓扑数据泛化与处理

San Kim, Eunjung Joo, Jusung Ha, Jaekwang Kim
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引用次数: 0

摘要

由于信息技术的发展,对数据处理的要求越来越高,数据处理方法也随之发展。具体来说,个人创建的数据正在通过社交媒体服务非常迅速地生成,因此,它们在服务个性化中具有重要意义。个人数据涉及非常复杂的关系和各种列表。使用传统的关系表模型开发复杂关系列表的数据系统是很困难的。有几种方法可以解决关系表模型中的这一限制。图结构就是这样一种新兴的方法。在图数据中,数据中的每个对象构成一个节点,对象之间的关系构成链接。图数据结构已用于商业产品,如Google Cayley和Amazon Neptune。在本研究中,我们将图数据结构推广到拓扑数据结构,并演示了一种将拓扑数据转换为句子结构的方法。我们建议使用查询函数,并提供相关示例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Generalizing and Processing Topological Data using Sentence Data Structure
Data-processing methods have evolved because of the high demand due to the development of information technology. Specifically, data created by individuals are being generated very rapidly through social-media services, and thus, they assume importance in service personalization. Personal data involve very complex relations and various lists. It is difficult to develop a data system for complex relational lists, using the traditional relational-table model. There are several approaches to addressing this limitation in the relational-table model. The graph structure is one such emerging approach. In graph data, each object in the data constitutes a node, and relations between objects constitute links. The graph data structure has been used in commercial products, such as Google Cayley and Amazon Neptune. In this study, we generalize the graph data structure to a topological data structure and demonstrate a method to transform topological data into a sentence structure. We suggest the use of query functions and provide relevant examples.
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