1School of Computer Science and Technology, Southwest University of Science and Technology University, Mianyang 621010, China 2Institute of Chemical Materials, China Academy of Engineering Physics, Mianyang 621900, China 3Chengdu Library and Information Center, Chinese Academy of Sciences, Chengdu 610041, China
[Objective] This paper tries to obtain and use the knowledge of formula design principle, component correlation and preparation technology, aiming to improve the process of explosive design. [Context] Our study organizes the scattered and complex knowledge for explosive formula design and visualizes design process for researchers. [Objective] We took the formulation of polymer bonded explosive as an example and built the knowledge graph of explosive formula with NLP technology. Then, we designed different visual analysis methods for each topic's knowledge graph. [Results] The new knowledge graph presented the related expression of structured and unstructured knowledge for researchers. We examined effectiveness of the proposed method with formulation of polymer bonded explosive, and found it helped researchers obtain the required formula design knowledge effectively. [Conclusions] This study offers practical solutions for researchers to use the knowledge of explosive formula design.
( Peng Lijuan, Yang Chunming, Wang Donglei, et al. Progress and Prospect of Energetic Materials Database[C]// Proceedings of the 1st Weapon Engineering Conference. 2017.)
( Xu Zenglin, Sheng Yongpan, He Lirong, et al. Review on Knowledge Graph Techniques[J]. Journal of University of Electronic Science and Technology of China, 2016, 45(4):589-606.)
[3]
Sun K, Liu Y H, Guo Z C, et al. EduVis: Visualization for Education Knowledge Graph Based on Web Data[C]// Proceedings of the 9th International Symposium on Visual Information Communication and Interaction. 2016: 138-139.
[4]
Dou J H, Qin J Y, Jin Z X, et al. Knowledge Graph Based on Domain Ontology and Natural Language Processing Technology for Chinese Intangible Cultural Heritage[J]. Journal of Visual Languages & Computing, 2018, 48:19-28.
( Zhang Ye, Jia Yuting, Fu Luoyi, et al. AceMap Academic Map and AceKG Academic Knowledge Graph for Academic Data Visualization[J]. Journal of Shanghai Jiaotong University, 2018, 52(10):1357-1362.)
( Yan Ziming, Du Debin, Liu Chengliang, et al. Visualization Analysis of Mapping Knowledge Domain on Western Geography of Innovation[J]. Acta Geographica Sinica, 2018, 73(2):362-379.)
doi: 10.11821/dlxb201802011
( Yang Haici, Wang Jun. Visualizing Knowledge Graph of Academic Inheritance in Song Dynasty[J]. Data Analysis and Knowledge Discovery, 2019, 3(6):109-116.)
[8]
Xu L Y, Fernando Z T, Zhou X, et al. LogCanvas: Visualizing Search History Using Knowledge Graphs [C]//Proceedings of the 41st International ACM SIGIR Conference on Research & Development in Information Retrieval. 2018: 1289-1292.
[9]
Ge T, Wang Y F, de Melo G, et al. Visualizing and Curating Knowledge Graphs over Time and Space [C]//Proceedings of ACL-2016 System Demonstrations. 2016: 25-30.
[10]
Li Y, Zhao J J, Yang L P, et al. Construction, Visualization and Application of Knowledge Graph of Computer Science Major [C]//Proceedings of the 2019 International Conference on Big Data and Education. 2019: 43-47.
[11]
Xu D W, Wang L, Wang X, et al. KG3D: An Interactive 3D Visualization Tool for Knowledge Graphs [C]//Proceedings of International Conference on Advanced Data Mining and Applications. Springer, Cham, 2019: 886-889.
[12]
He X, Zhang R, Rizvi R F, et al. ALOHA: Developing an Interactive Graph-Based Visualization for Dietary Supplement Knowledge Graph Through User-centered Design[J]. BMC Medical Informatics and Decision Making, 2019, 19(4):1-18.
doi: 10.1186/s12911-018-0723-6
[13]
Szekely P, Knoblock C A, Slepicka J, et al. Building and Using a Knowledge Graph to Combat Human Trafficking [C]//Proceedings of International Semantic Web Conference. Springer, Cham, 2015: 205-221.
[14]
Liu H, Li Y F, Hong R, et al. Knowledge Graph Analysis and Visualization of Research Trends on Driver Behavior[J]. Journal of Intelligent & Fuzzy Systems, 2020, 38(1):495-511.
[15]
Yu T, Li J H, Yu Q, et al. Knowledge Graph for TCM Health Preservation: Design, Construction, and Applications[J]. Artificial Intelligence in Medicine, 2017, 77:48-52.
doi: 10.1016/j.artmed.2017.04.001
[16]
Henry N, Fekete J D, McGuffin M J. NodeTrix: A Hybrid Visualization of Social Networks[J]. IEEE Transactions on Visualization and Computer Graphics, 2007, 13(6):1302-1309.
doi: 10.1109/TVCG.2007.70582
[17]
Bach B, Pietriga E, Liccardi I, et al. OntoTrix: A Hybrid Visualization for Populated Ontologies [C]//Proceedings of the 20th International Conference Companion on World Wide Web. 2011: 177-180.
[18]
Lin C C, Deng D J, Jhong S Y. A Triangular NodeTrix Visualization Interface for Overlapping Social Community Structures of Cyber-physical-social Systems in Smart Factories[J]. IEEE Transactions on Emerging Topics in Computing, 2020, 8(1):58-68.
doi: 10.1109/TETC.6245516
[19]
Angori L, Didimo W, Montecchiani F, et al. ChordLink: A New Hybrid Visualization Model [C]//Proceedings of International Symposium on Graph Drawing and Network Visualization. Springer, Cham, 2019: 276-290.
[20]
Lafferty J, McCallum A, Pereira F C N. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data [C]//Proceedings of the 18th International Conference on Machine Learning. 2001: 282-289.
[21]
Zeng D J, Liu K, Lai S W, et al. Relation Classification via Convolutional Deep Neural Network [C]//Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers. 2014: 2335-2344.
