Research on the Clustering Method of Agricultural Scientific Data Based on the Author’s Scientific Research Relationship
Focusing on semantic parse and bias problems during the clustering process of agricultural scientific data, a clustering method for agricultural scientific data based on author’s scientific research relationship is proposed in this paper. Meanwhile, an assessment algorithm of the scientific research relationship based on co-author ship and authors’ inter-citation is put forward. Finally, the experimental results proved that the proposed clustering method for the agricultural scientific data can effectively improve error classification caused by semantic parse and bias.
KeywordsScientific data Data clustering Scientific research relationship
Funding for this research was provided by national science and technology basic conditions platform ‘‘The agricultural science data sharing Centre” (2005DKA31800) and technology Innovation Engineering project of CAAS “Research on agricultural cognitive computing and supercomputing” (CAAS-ASTIP-2016-AII).
- 1.Wang, X., Yin, X.: A study on scientific data clustering based on improved FIHC. J. Shanxi Datong Univ. (Nat. Sci.) 30, 4–7 (2014)Google Scholar
- 3.Zhu, Y.: An Empirical Study on Correlation Degree Model of Scholars Based on Co Authorship and Reference relation Analysis, Library Science and Informatics, vol. 22, pp. 97–103 (2015)Google Scholar
- 4.Wan, J., Dingfeng, W.: Design and improvement of single sign-on technology for agriculture information services. Comput. Technol. Dev. 26(5), 191–196 (2016)Google Scholar
- 5.Wu, S.: The Improvement of Academic Retrieval System Based on Citation Analysis (2012)Google Scholar
- 7.Yadav, D.K.: Comparative Analysis of Clustering Current Research, vol. 7, pp. 18361–18364 (2015)Google Scholar
- 8.Jassar, K.K., Dhindsa, K.S.: Comparative study and performance analysis of clustering algorithms. IJCA Proc. Int. Conf. ICT Healthcare ICTHC 2015(1), 1–6 (2016)Google Scholar
- 9.Wang, W., et al.: Relationship between academic cooperation and research output based on academic journal papers: a research taking the library and information field as an example. J. Intell. (2017)Google Scholar
- 10.Yang, R., Zhang, M.: A research review on academic relationship of authors. Libr. Inf. Serv. (2016)Google Scholar
- 11.Zhang, S.H., et al.: Study on the relationship between college students’ academic activities and academic performance. Value Eng. (2018)Google Scholar
- 12.Wang, X.H., Yin, X.B., Wen-Yan, B.O.: Improved scientific data clustering algorithm based on FIHC. J. Shanxi Datong Univ. (2014)Google Scholar
- 14.Husic, B.E., Schlueter-Kuck, K.L., Dabiri, J.O.: Amplifying state dissimilarity leads to robust and interpretable clustering of scientific data. Mach. Learn. (2018)Google Scholar