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An Efficient Tool for Semantic Biomedical Document Analysis

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Advances in Intelligent Information Hiding and Multimedia Signal Processing

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 212))

Abstract

With the rapid growth of biomedical documents, finding out interested documents efficiently becomes a challenging for researchers. To improve the efficiency and display biomedical information in a more direct way, a medical knowledge graph-based semantic text analysis tool is developed. This tool is based on improved bag-of-words and ontology-based semantic text mining algorithms, supporting visualized biomedical conception and documents analysis. The testing results show that proposed models perform well on medical documents clustering, accuracy in different dataset is above 82% and the best one reaches 96%.

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Acknowledgements

This research was supported by the National Natural Science Foundation of China (Grant No. 61702324 and Grant No. 61911540482) in People’s Republic of China, and by the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (NRF-2019K2A9A2A06020672).

Author information

Authors and Affiliations

  1. College of Information Engineering, Shanghai Maritime University, Shanghai, 201306, China

    Meijing Li & Jingyu Hu

  2. Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, 700000, Vietnam

    Keun Ho Ryu

  3. Department of Computer Science, College of Electrical and Computer Engineering, Chungbuk National University, Cheongju, 28644, Korea

    Keun Ho Ryu

Authors
  1. Meijing Li
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  2. Jingyu Hu
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  3. Keun Ho Ryu
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Corresponding author

Correspondence to Keun Ho Ryu .

Editor information

Editors and Affiliations

  1. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, Shandong, China

    Jeng-Shyang Pan

  2. Northeast Electric Power University, Jilin, Jilin, China

    Jianpo Li

  3. College of Electrical & Computer Engineering, Chungbuk National University, Cheongju, Korea (Republic of)

    Keun Ho Ryu

  4. Fujian University of Technology, Fuzhou, China

    Zhenyu Meng

  5. Faculty of Sciences, University of Novi Sad, Novi Sad, Serbia

    Aleksandra Klasnja-Milicevic

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Li, M., Hu, J., Ryu, K.H. (2021). An Efficient Tool for Semantic Biomedical Document Analysis. In: Pan, JS., Li, J., Ryu, K.H., Meng, Z., Klasnja-Milicevic, A. (eds) Advances in Intelligent Information Hiding and Multimedia Signal Processing. Smart Innovation, Systems and Technologies, vol 212. Springer, Singapore. https://doi.org/10.1007/978-981-33-6757-9_63

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