Springer Nature is making Coronavirus research free. View research | View latest news | Sign up for updates

Building thesaurus-based knowledge graph based on schema layer

  • 557 Accesses

  • 2 Citations


Google proposed the concept of knowledge graph to improve the quality of searching results in 2012, so the knowledge graph brought a hot topic in the field of academic and industry. The knowledge graph can effectively improve the searching quality and the accuracy of Q & A system, which is a hot issue. With the help of agricultural experts, this paper based on the Agricultural Thesaurus, determines the rules for judging whether a thesaurus is a concept or an entity, establishes maps from Agricultural Thesaurus to the agricultural knowledge graph schema layer and the data layer. Therefore, the large-scale automatic building is realized from the Agricultural Thesaurus to the agricultural knowledge graph. In order to effectively manage and utilize triples, this paper proposes a mathematical model for the management of triples with the RDF-based triple storage pattern, which lays the solid foundation for the semantic-based agricultural information retrieving and the construction of the Q & A system.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10


  1. 1.

    Haofen, W.: Large scale knowledge graph technology. Commun. CCF 10(3), 64–68 (2014) (in chinese)

  2. 2.

    Bollacker, K., Evans, C., Paritosh, P., et al.: Freebase: a collaboratively created graph database for structuring human knowledge. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of data, pp. 1247–1250. ACM (2008)

  3. 3.

    Lehmann, J., Isele, R., Jakob, M., et al.: DBpedia—a Large-scale, multilingual knowledge base extracted from Wikipedia. Semant. Web. J. 6(2), 167–195 (2014)

  4. 4.

    Hoffart, J., Suchanek, F.M., Berberich, K., et al.: YAGO2: a spatially and temporally enhanced knowledge base from Wikipedia. Artif. Intell. 194, 28–61 (2013)

  5. 5.

    Suchanek, F.M., Kasneci, G., Weikum, G., et al.: Yago: a core of semantic knowledge. Hierarchically Organized Syst. Theory Pract. 272(2), 181–221 (2007)

  6. 6.

    Xu, Z., Zhang, H., Hu, C., Mei, L., Xuan, J., Raymond Choo, K.-K., Sugumaran, V., Zhu, Y.: Building knowledge base of urban emergency events based on crowd sourcing of social media. Concurrency Comput. Pract. Exp. 28(15), 4038–4052 (2016)

  7. 7.

    Xu, Z., Wei, X., Liu, Y., Mei, L., Hu, C., Raymond Choo, K.-K., Zhu, Y., Sugumaran, V.: Building the search pattern of web users using conceptual semantic space model. IJWGS 12(3), 328–347 (2016)

  8. 8.

    Xu, Z., Chen, H.: The semantic analysis of knowledge map for the traffic violations from the surveillance video big data. Comput. Syst. Sci. Eng. 30(5) (2015)

  9. 9.

    Lauser, B., Sini, M.: From AGROVOC to the agricultural ontology service/concept server: an OWL model for creating ontologies in the agricultural domain. In: Dublin Core Conference Proceedings (2006)

  10. 10.

    Soergel, D., Lauser, B., Liang, A.C., et al.: Reengineering thesauri for new applications: the AGROVOC example. J. Digital Inf. 4(4) (2004)

  11. 11.

    Jing, T.: Research on thesaurus transfer into the ontology. Inf. Stud. Theory Appl. 27(6), 642–645 (2004)

  12. 12.

    Assem, M.V., Menken, M.R., Schreiber, G., et al.: A method for converting thesauri to RDF/OWL. Lect. Notes Comput. Sci. 3298, 17–31 (2004)

  13. 13.

    Zhi-an, Y., Yue, W.: Thesaurus-based oil field ontology construction method. Comput. Syst. Appl. 24(9), 91–96 (2015)

  14. 14.

    Chunyan, L.: Research on SKOS-Based Thesaurus Transfer into the Ontology in the Semantic Web Environment. Jilin University (2006)

  15. 15.

    Yi, L., Bo, Z.: Construction and application of government information ontology based on government thesaurus. Comput. Eng. Des. 31(3), 521–524 (2010)

  16. 16.

    Jianjun, G.: Method research on Chinese medical ancient literature ontology modeling. China Academy of Chinese Medical Sciences (2006)

  17. 17.

    Aimin, T., Qin, Z., Jing, F.: Thesaurus-based domain ontology construction research. New Technol. Library Inf. Serv. 21(4), 1–5 (2005)

  18. 18.

    Jianwu, X., Miao, G., Tuo, W.: Research on SKOS-based defense science and technology thesaurus transfer into the ontology. J. China Soc. Sci. Technical Inf. 28(3), 310–317 (2011)

  19. 19.

    Yun, X., Dongyi, Y., Wende, Z.: Construction research on domain ontology based on the “China Classified Thesaurus”. J. Intell. 26(3), 15–18 (2007)

  20. 20.

    Xinhong, Z., Zhong, M., Yin, J., et al.: Research on joint construction and sharing system research based on chinese thesaurus ontology. J. China Soc. Sci. Technical Inf. 27(3), 386–394 (2008)

  21. 21.

    Xinhong, Z.: Chinese thesaurus ontology: fusion thesaurus and ontology. New Technol. Library Inf. Serv. 1, 34–43 (2009)

  22. 22.

    Ministry of Agriculture Information Institute (1994) Agricultural Thesaurus. China Agriculture Press, Beijing (1994)

  23. 23.

    Chunpei, H., Sijing, L.: Prospects and development of agricultural thesaurus and ontology in China. J. Library Inf. Sci. Agric. 4, 16–19 (2003)

  24. 24.

    Chun, C.: Construction and transformation of agricultural information management ontology. Chinese Academy of Agricultural Sciences (2004)

  25. 25.

    Guojian, X.: Research and implementation of agricultural thesaurus transfer into the ontology system. Chinese Academy of Agricultural Sciences (2008)

  26. 26.

    Guojian, X., Ruixue, Z., Liang, Z., et al.: Transformation and application of SKOS based on Agricultural thesaurus. J. Library Inf. Sci. Agric. 10, 16–20 (2012)

  27. 27.

    Guojian, X., Ruixue, Z., Yuantao, K., et al.: Research and practice on agricultural thesaurus linked data. J. Library Inf. Sci. Agric. 29(11), 8–14 (2013)

  28. 28.

    Qian, S.: Research on domain ontology modeling method based on thesaurus. Shandong University (2007)

Download references


Our work has been fully supported by the National Science and Technology Funding Program (2012BAD35807), the Hunan Province’s Key Science and Technology Project (2016NK2118), as well as the Hunan Education Authority’s Science Research Project (13C389).

Author information

Correspondence to Kui Fang.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Qiao, B., Fang, K., Chen, Y. et al. Building thesaurus-based knowledge graph based on schema layer. Cluster Comput 20, 81–91 (2017).

Download citation


  • Knowledge graph
  • Agricultural thesaurus
  • Schema layer
  • Triple
  • Mathematical model