Cn-MAKG: China Meteorology and Agriculture Knowledge Graph Construction Based on Semi-structured Data

In this paper, a method of constructing China meteorology and agriculture knowledge graph based on semi-structured data is proposed. Firstly, demand analysis, determine the boundary of knowledge, according to which design the schema of Cn-MAKG. Then the semi-structured knowledge data is preprocessed...

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Bibliographic Details
Published in2018 IEEE ACIS 17th International Conference on Computer and Information Science (ICIS) pp. 692 - 696
Main Authors Chenglin, Qi, Qing, Song, Pengzhou, Zhang, Hui, Yuan
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2018
Subjects
Agriculture
data processing
Indexes
Knowledge acquisition
knowledge graph
knowledge storage
Meteorology
meteorology and agriculture
schema
Semantics
semi-structured data
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DOI10.1109/ICIS.2018.8466485

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Summary:In this paper, a method of constructing China meteorology and agriculture knowledge graph based on semi-structured data is proposed. Firstly, demand analysis, determine the boundary of knowledge, according to which design the schema of Cn-MAKG. Then the semi-structured knowledge data is preprocessed in accordance with the standard indexes in the domain of meteorology and agriculture. Finally, the graph database Neo4j is used to store the knowledge graph, so as to realize the construction of Cn-MAKG. At present, the knowledge graph has been successfully applied to the automatic generation of crop meteorological reports.
DOI:10.1109/ICIS.2018.8466485