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Bert-Based Latent Semantic Analysis (Bert-LSA): A Case Study on Geospatial Data Technology and Application Trend Analysis

文献类型：期刊论文

作者Cheng, Quanying2,3; Zhu, Yunqiang1,2; Song, Jia1,2; Zeng, Hongyun4; Wang, Shu2; Sun, Kai2; Zhang, Jinqu5
刊名APPLIED SCIENCES-BASEL
出版日期2021-12-01
卷号11期号:24页码:13
关键词trend analysis topic modeling Bert geospatial data technology and application
DOI10.3390/app112411897
通讯作者Zhu, Yunqiang(zhuyq@lreis.ac.cn)
英文摘要Geospatial data is an indispensable data resource for research and applications in many fields. The technologies and applications related to geospatial data are constantly advancing and updating, so identifying the technologies and applications among them will help foster and fund further innovation. Through topic analysis, new research hotspots can be discovered by understanding the whole development process of a topic. At present, the main methods to determine topics are peer review and bibliometrics, however they just review relevant literature or perform simple frequency analysis. This paper proposes a new topic discovery method, which combines a word embedding method, based on a pre-trained model, Bert, and a spherical k-means clustering algorithm, and applies the similarity between literature and topics to assign literature to different topics. The proposed method was applied to 266 pieces of literature related to geospatial data over the past five years. First, according to the number of publications, the trend analysis of technologies and applications related to geospatial data in several leading countries was conducted. Then, the consistency of the proposed method and the existing method PLSA (Probabilistic Latent Semantic Analysis) was evaluated by using two similar consistency evaluation indicators (i.e., U-Mass and NMPI). The results show that the method proposed in this paper can well reveal text content, determine development trends, and produce more coherent topics, and that the overall performance of Bert-LSA is better than PLSA using NPMI and U-Mass. This method is not limited to trend analysis using the data in this paper; it can also be used for the topic analysis of other types of texts.
WOS关键词BIBLIOMETRIC ANALYSIS
资助项目National Natural Science Foundation of China[42050101] ; National Natural Science Foundation of China[41771430] ; National Natural Science Foundation of China[41631177] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA23100100]
WOS研究方向Chemistry ; Engineering ; Materials Science ; Physics
语种英语
WOS记录号WOS:000735327900001
出版者MDPI
资助机构National Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences
源URL[http://ir.igsnrr.ac.cn/handle/311030/169154]  
专题中国科学院地理科学与资源研究所
通讯作者Zhu, Yunqiang
作者单位1.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
3.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
4.Yunnan Univ, Sch Earth Sci, Kunming 650500, Yunnan, Peoples R China
5.South China Normal Univ, Sch Comp Sci, Guangzhou 510000, Peoples R China
推荐引用方式
GB/T 7714		 Cheng, Quanying,Zhu, Yunqiang,Song, Jia,et al. Bert-Based Latent Semantic Analysis (Bert-LSA): A Case Study on Geospatial Data Technology and Application Trend Analysis[J]. APPLIED SCIENCES-BASEL,2021,11(24):13.
APA Cheng, Quanying.,Zhu, Yunqiang.,Song, Jia.,Zeng, Hongyun.,Wang, Shu.,...&Zhang, Jinqu.(2021).Bert-Based Latent Semantic Analysis (Bert-LSA): A Case Study on Geospatial Data Technology and Application Trend Analysis.APPLIED SCIENCES-BASEL,11(24),13.
MLA Cheng, Quanying,et al."Bert-Based Latent Semantic Analysis (Bert-LSA): A Case Study on Geospatial Data Technology and Application Trend Analysis".APPLIED SCIENCES-BASEL 11.24(2021):13.

入库方式： OAI收割

来源：地理科学与资源研究所

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