{"title":"基于句子数据结构的拓扑数据泛化与处理","authors":"San Kim, Eunjung Joo, Jusung Ha, Jaekwang Kim","doi":"10.1109/IMCOM51814.2021.9377358","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":275121,"journal":{"name":"2021 15th International Conference on Ubiquitous Information Management and Communication (IMCOM)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Generalizing and Processing Topological Data using Sentence Data Structure\",\"authors\":\"San Kim, Eunjung Joo, Jusung Ha, Jaekwang Kim\",\"doi\":\"10.1109/IMCOM51814.2021.9377358\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":275121,\"journal\":{\"name\":\"2021 15th International Conference on Ubiquitous Information Management and Communication (IMCOM)\",\"volume\":\"116 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 15th International Conference on Ubiquitous Information Management and Communication (IMCOM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IMCOM51814.2021.9377358\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 15th International Conference on Ubiquitous Information Management and Communication (IMCOM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMCOM51814.2021.9377358","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.