Many ontologies are provided to representing semantic sensors data.However,heterogeneity exists in different sensors which makes some service operators of Internet of Thing(IoT) difficult(such as such as semantic infe...Many ontologies are provided to representing semantic sensors data.However,heterogeneity exists in different sensors which makes some service operators of Internet of Thing(IoT) difficult(such as such as semantic inferring,non-linear inverted index establishing,service composing) .There is a great deal of research about sensor ontology alignment dealing with the heterogeneity between the different sensor ontologies,but fewer solutions focus on exploiting syntaxes in a sensor ontology and the pattern of accessing alignments.Our solution infers alignments by extending structural subsumption algorithms to analyze syntaxes in a sensor ontology,and then combines the alignments with the SKOS model to construct the integration sensor ontology,which can be accessed via the IoT.The experiments show that the integration senor ontology in the SKOS model can be utilized via the IoT service,and the accuracy of our prototype,in average,is higher than others over the four real ontologies.展开更多
本文以Bates & Mac Whinney (1989)的句子理解竞争模型为理论基础,考察不同英语水平的英、汉双语者在理解汉语和英语句子时如何使用词序和生命性这两条线索。实验结果表明:对于英、汉双语者而言,生命性和词序都是理解两种语言的重...本文以Bates & Mac Whinney (1989)的句子理解竞争模型为理论基础,考察不同英语水平的英、汉双语者在理解汉语和英语句子时如何使用词序和生命性这两条线索。实验结果表明:对于英、汉双语者而言,生命性和词序都是理解两种语言的重要线索,但生命性的作用更大,解释力更强;词序作用有随着双语者英语水平的提高而增强的趋势,但这种趋势还不够稳定,高级双语组依赖词序的程度有所减弱;在生命性维持不变从而不能决定句子的理解时,双语者使用了更为普遍的语义线索。展开更多
基金Supported by National Natural Science Foundation of China(No.61601039)financially supported by the State Key Research Development Program of China(Grant No.2016YFC0801407)+3 种基金financially supported by the Natural Science Foundation of Beijing Information Science & Technology University(No.1625008)financially supported by the Opening Project of Beijing Key Laboratory of Internet Culture and Digital Dissemination Research(NO.ICDD201607)Open Foundation of State key Laboratory of Networking and Switching Technology(Beijing University of Posts and Telecommunications)(NO.SKLNST-2016-2-08)financially supported by the Importation and Development of High-Caliber Talents Project of Beijing Municipal Institutions(Grant No.CIT&TCD201504056)
文摘Many ontologies are provided to representing semantic sensors data.However,heterogeneity exists in different sensors which makes some service operators of Internet of Thing(IoT) difficult(such as such as semantic inferring,non-linear inverted index establishing,service composing) .There is a great deal of research about sensor ontology alignment dealing with the heterogeneity between the different sensor ontologies,but fewer solutions focus on exploiting syntaxes in a sensor ontology and the pattern of accessing alignments.Our solution infers alignments by extending structural subsumption algorithms to analyze syntaxes in a sensor ontology,and then combines the alignments with the SKOS model to construct the integration sensor ontology,which can be accessed via the IoT.The experiments show that the integration senor ontology in the SKOS model can be utilized via the IoT service,and the accuracy of our prototype,in average,is higher than others over the four real ontologies.
文摘本文以Bates & Mac Whinney (1989)的句子理解竞争模型为理论基础,考察不同英语水平的英、汉双语者在理解汉语和英语句子时如何使用词序和生命性这两条线索。实验结果表明:对于英、汉双语者而言,生命性和词序都是理解两种语言的重要线索,但生命性的作用更大,解释力更强;词序作用有随着双语者英语水平的提高而增强的趋势,但这种趋势还不够稳定,高级双语组依赖词序的程度有所减弱;在生命性维持不变从而不能决定句子的理解时,双语者使用了更为普遍的语义线索。
