Knowledge map construction of multi-source heterogeneous contaminated site data

DOI

10.2991/978-94-6463-102-9_11How to use a DOI?

Keywords

soil pollution; multi-source heterogeneity; knowledge atlas; visualization

Abstract

The retirement and relocation of urban industrial enterprises has led to the retirement of a large number of contaminated sites. Aiming at the problem that the data related to the contaminated site comes from many different sources and has different structures, and it is difficult to explore the potential correlation between the data through the existing management methods, this paper proposes a knowledge map construction method for multi-source heterogeneous data of the contaminated site. According to the different structures of contaminated site data, we use the knowledge construction theory to select appropriate entity recognition, relationship recognition and knowledge fusion methods to extract various types of information of contaminated sites and establish semantic networks. The knowledge map constructed for a contaminated site in Northeast China contains 3840 contaminated site entities including site information, enterprise information and soil information, and the corresponding association relationship is 4768. Practice has proved that the proposed knowledge map construction method can effectively and intuitively represent the potential association relationship between contaminated site data, and provide corresponding technical support and decision-making information for the relevant departments of contaminated site restoration and management.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Xingchen Li
AU  - Jianqin Zhang
AU  - Lina Fan
AU  - Xinzhi Li
AU  - Huizhong Jiang
AU  - Nan Lu
PY  - 2022
DA  - 2022/12/29
TI  - Knowledge map construction of multi-source heterogeneous contaminated site data
BT  - Proceedings of the 2022 2nd International Conference on Business Administration and Data Science (BADS 2022)
PB  - Atlantis Press
SP  - 78
EP  - 85
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-102-9_11
DO  - 10.2991/978-94-6463-102-9_11
ID  - Li2022
ER  -