{"title":"Semi-automatic metadata annotation of Web of Things with knowledge base","authors":"Yunong Yang, Zhenyu Wu, Xinning Zhu","doi":"10.1109/ICNIDC.2016.7974549","DOIUrl":null,"url":null,"abstract":"Integrating semantic technology to the Web of Things (WoT) facilitates the creation of a networked knowledge infrastructure with more interoperable data from both physical and cyber world. However, most of current solutions relies on manual methods based on domain-specific ontology, which is only suitable for domain expert and developers but not compatible with large-scale knowledge construction. This paper proposes a semi-automatic annotation framework for the metadata representation of WoT resource. This framework is based on a probabilistic graphical model to collectively infer entities, classes and relations from schematic WoT resources mapping to domain independent knowledge base. A proof-of-concept implementation and performance evaluation are illustrated to show a feasibility of our method.","PeriodicalId":439987,"journal":{"name":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNIDC.2016.7974549","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Integrating semantic technology to the Web of Things (WoT) facilitates the creation of a networked knowledge infrastructure with more interoperable data from both physical and cyber world. However, most of current solutions relies on manual methods based on domain-specific ontology, which is only suitable for domain expert and developers but not compatible with large-scale knowledge construction. This paper proposes a semi-automatic annotation framework for the metadata representation of WoT resource. This framework is based on a probabilistic graphical model to collectively infer entities, classes and relations from schematic WoT resources mapping to domain independent knowledge base. A proof-of-concept implementation and performance evaluation are illustrated to show a feasibility of our method.