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Research on Construction Methods of Big Data Semantic Model

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Big data integration process faced structural heterogeneity and semantic heterogeneity problems. An ontology is an explicit specification of a conceptualization, which is the core of semantic web technologies that can be used to describe the semantics of the metadata. This paper builds a big data model based on ontology by exploiting semantic web technology, and propose an ontology-based semantic model and ontology-based Key/Value storage model, meanwhile giving detailed steps for building the model. The model proposed try to solve the issue of understanding between heterogeneous data systems. Finally, we give an example of the semantic model application, which has been verified on HBase-based prototype system

“knowledge” [4]. Ontology is the core of the Semantic Web technology, which is also an important method to
conceptualize domain knowledge and modeling that can be used to describe the semantics of the data. The introduction of ontology to integrate thinking, intelligent retrieval of big data, can provide a new idea for big data research and application. Currently, the research by combining the ontology with the big data application is still rare. This paper aims at the characteristics of big data, building a data model based on ontology, proposed a solution to the structural heterogeneity and semantic heterogeneity of big data

Big data generally refers to large-scale, rapid changes in many types. The data sets are usually integrated
data from different sources in a structured, semi-structured, and unstructured data collection. The unstructured and
semi-structured data more than 85%. Big Data applications often involve multiple data sources, there are structural
heterogeneity and semantic heterogeneity problems between the data sources [2]. Refers to structural heterogeneity of different data stored in the data model could not be directly mapped to each other. Semantic heterogeneous data that describe the terms inconsistent with each other could not understand each other, and unable to reflect the link between the data sets. How to solve the problem of structural heterogeneity and semantic heterogeneity is one of the major challenges facing big data

by :Li Kang, Li Yi, LIU Dong

information file :English langauge /6 page/size:670k

download link :click

کاری از :Li Kang, Li Yi, LIU Dong

اطلاعات فایل :زبان انگلیسی /6صفحه / حجم :670 K

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