用信息流和知网构建大数据语义共享通道研究
大数据除了数据量巨大之外,而且具有类型繁多、信息表示结构各异、语法语义冲突和动态变化等特点,故难以共享.为了共享大数据中的语义信息,必须有满足动态、异构和大规模等特点的共享机制.本文分析了信息流(InformationFlow)理论,也称为通道理论(ChannelTheory),以及知网(HowNet)技术,二者相结合可以作为大数据语义理解的基础.提出了用信息流理论和知网共同构建基于语义的大数据共享通道的观点,用信息源分类本体、社团本体和通道本体作为语义共享的核心机制,通过信息射构成大数据语义共享通道.并用职业信息共享为案例进行初步实践,结果体现了所构建通道的有效性....
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Published in | 广东工业大学学报 Vol. 34; no. 3; pp. 30 - 35 |
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Main Author | |
Format | Journal Article |
Language | Chinese |
Published |
广东轻工职业技术学院 机电系,广东 广州,510300%广东工业大学 计算机学院,广东 广州,510006
2017
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Subjects | |
Online Access | Get full text |
ISSN | 1007-7162 |
DOI | 10.12052/gdutxb.170026 |
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Summary: | 大数据除了数据量巨大之外,而且具有类型繁多、信息表示结构各异、语法语义冲突和动态变化等特点,故难以共享.为了共享大数据中的语义信息,必须有满足动态、异构和大规模等特点的共享机制.本文分析了信息流(InformationFlow)理论,也称为通道理论(ChannelTheory),以及知网(HowNet)技术,二者相结合可以作为大数据语义理解的基础.提出了用信息流理论和知网共同构建基于语义的大数据共享通道的观点,用信息源分类本体、社团本体和通道本体作为语义共享的核心机制,通过信息射构成大数据语义共享通道.并用职业信息共享为案例进行初步实践,结果体现了所构建通道的有效性. |
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Bibliography: | big data; semantics; information flow; channel; HowNet In addition to the huge amount of data,wide range of data,different information structure,grammatical and semantic conflicts,highly heterogeneous and dynamic,big data is difficult to share.In order to share the semantic information in big data,there must be a sharing mechanism with dynamic,heterogeneous and large-scale features to enable users to share semantic information of big data.Information Flow theory,also called Channel Theory,as well as HowNet,have been analyzed.Combine them provide us bases of big data semantic understanding.The idea of building the big data semantics sharing channel based both on the information flow theory and Hownet is present.Information resources classify ontology,society ontology and channel ontology act as the kernel of the semantic sharing.Build the big data semantic sharing channel by infomorphisms.Professional information sharing as case study has carried on the preliminary practice.The experiment results show the effec |
ISSN: | 1007-7162 |
DOI: | 10.12052/gdutxb.170026 |