TY - GEN
T1 - Utilizing Text Mining to Extract Critical Indicators for Wetland Health Evaluation
AU - Chen, Lan
AU - Ni, Guoqing
AU - Lu, Shaoyu
AU - Novianto, Didit
AU - Liu, Chao
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
PY - 2024
Y1 - 2024
N2 - Wetland is one of the important ecological systems of the earth, it boasts necessary functions, such as, regulating climate, water supply, purifying water, protecting biodiversity and others. Nowadays, wetland health assessment has become a major direction in wetland research, so the optimization of wetland evaluation is significant for sustainable global development. However, most wetland assessments don’t have agreed indicators and criteria. So, this study aims to use data mining technology to explore the major factors related to relationships about evaluation. Web of Science, EI, Scopus are used to search for training samples, the topic word was “wetland health”, finally 100 articles were selected. These articles compose a corpus which is the basis for text mining. The study mains to apply the online data and web-based text mining technique is proposed to evaluate wetland health status and explore new ideas for wetland health evaluation. Results show that “groundw”, “people”, soil, policy and so on are important and can be called key words. Then, these key words can be used as indicators and they can provide data to the further study.
AB - Wetland is one of the important ecological systems of the earth, it boasts necessary functions, such as, regulating climate, water supply, purifying water, protecting biodiversity and others. Nowadays, wetland health assessment has become a major direction in wetland research, so the optimization of wetland evaluation is significant for sustainable global development. However, most wetland assessments don’t have agreed indicators and criteria. So, this study aims to use data mining technology to explore the major factors related to relationships about evaluation. Web of Science, EI, Scopus are used to search for training samples, the topic word was “wetland health”, finally 100 articles were selected. These articles compose a corpus which is the basis for text mining. The study mains to apply the online data and web-based text mining technique is proposed to evaluate wetland health status and explore new ideas for wetland health evaluation. Results show that “groundw”, “people”, soil, policy and so on are important and can be called key words. Then, these key words can be used as indicators and they can provide data to the further study.
KW - K-means
KW - Text Mining
KW - Wetland Evaluation
UR - http://www.scopus.com/inward/record.url?scp=85206200049&partnerID=8YFLogxK
U2 - 10.1007/978-981-97-2447-5_41
DO - 10.1007/978-981-97-2447-5_41
M3 - Conference contribution
AN - SCOPUS:85206200049
SN - 9789819724468
T3 - Lecture Notes in Electrical Engineering
SP - 265
EP - 270
BT - Advances in Computer Science and Ubiquitous Computing - Proceedings of CUTE/CSA 2023
A2 - Park, Ji Su
A2 - Yang, Laurence T.
A2 - Pan, Yi
A2 - Park, James J.
PB - Springer Science and Business Media Deutschland GmbH
T2 - 15th International Conference on Computer Science and its Applications, CSA 2023 and 17th KIPS International Conference on Ubiquitous Information Technologies and Applications, CUTE 2023
Y2 - 18 December 2023 through 20 December 2023
ER -