{"title":"链接式开放数据云对上下文感知服务的适用性分析","authors":"M. Hoffen, A. Uzun, Axel Küpper","doi":"10.1109/ICSC.2014.27","DOIUrl":null,"url":null,"abstract":"The amount of data within the Linking Open Data (LOD) cloud is steadily increasing and resembles a rich source of information. Since Context-aware Services (CAS) can highly benefit from background information, e.g., about the environment of a user, it makes sense to leverage that enormous amount of data already present in the LOD cloud to enhance the quality of these services. Within this work, the applicability of the LOD cloud as provider for contextual information to enrich CAS is investigated. For this purpose, non-functional criteria of discoverability and availability are analyzed, followed by a presentation of an overview of the different domains covered by the LOD cloud. In order to ease the process of finding a dataset that matches the information needs of a developer of a CAS, techniques for retrieving contents of LOD datasets are discussed and different approaches to condense the dataset to its most important concepts are shown.","PeriodicalId":175352,"journal":{"name":"2014 IEEE International Conference on Semantic Computing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Analyzing the Applicability of the Linking Open Data Cloud for Context-Aware Services\",\"authors\":\"M. Hoffen, A. Uzun, Axel Küpper\",\"doi\":\"10.1109/ICSC.2014.27\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The amount of data within the Linking Open Data (LOD) cloud is steadily increasing and resembles a rich source of information. Since Context-aware Services (CAS) can highly benefit from background information, e.g., about the environment of a user, it makes sense to leverage that enormous amount of data already present in the LOD cloud to enhance the quality of these services. Within this work, the applicability of the LOD cloud as provider for contextual information to enrich CAS is investigated. For this purpose, non-functional criteria of discoverability and availability are analyzed, followed by a presentation of an overview of the different domains covered by the LOD cloud. In order to ease the process of finding a dataset that matches the information needs of a developer of a CAS, techniques for retrieving contents of LOD datasets are discussed and different approaches to condense the dataset to its most important concepts are shown.\",\"PeriodicalId\":175352,\"journal\":{\"name\":\"2014 IEEE International Conference on Semantic Computing\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE International Conference on Semantic Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSC.2014.27\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Conference on Semantic Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSC.2014.27","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analyzing the Applicability of the Linking Open Data Cloud for Context-Aware Services
The amount of data within the Linking Open Data (LOD) cloud is steadily increasing and resembles a rich source of information. Since Context-aware Services (CAS) can highly benefit from background information, e.g., about the environment of a user, it makes sense to leverage that enormous amount of data already present in the LOD cloud to enhance the quality of these services. Within this work, the applicability of the LOD cloud as provider for contextual information to enrich CAS is investigated. For this purpose, non-functional criteria of discoverability and availability are analyzed, followed by a presentation of an overview of the different domains covered by the LOD cloud. In order to ease the process of finding a dataset that matches the information needs of a developer of a CAS, techniques for retrieving contents of LOD datasets are discussed and different approaches to condense the dataset to its most important concepts are shown.