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An integrated pipeline model for biomedical entity alignment

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Abstract

Biomedical entity alignment, composed of two sub-tasks: entity identification and entity-concept mapping, is of great research value in biomedical text mining while these techniques are widely used for name entity standardization, information retrieval, knowledge acquisition and ontology construction.

Previous works made many efforts on feature engineering to employ feature-based models for entity identification and alignment. However, the models depended on subjective feature selection may suffer error propagation and are not able to utilize the hidden information. With rapid development in health-related research, researchers need an effective method to explore the large amount of available biomedical literatures.

Therefore, we propose a two-stage entity alignment process, biomedical entity exploring model, to identify biomedical entities and align them to the knowledge base interactively. The model aims to automatically obtain semantic information for extracting biomedical entities and mining semantic relations through the standard biomedical knowledge base. The experiments show that the proposed method achieves better performance on entity alignment. The proposed model dramatically improves the F1 scores of the task by about 4.5% in entity identification and 2.5% in entity-concept mapping.

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Acknowledgements

This research was supported by the National Key Research and Development Program of China (2018YFB1003404), the National Natural Science Foundation of China (Grant Nos. 61672142, 61402213), the Fundamental Research Funds for the Central Universities (N150408001-3, N150404013), Natural Science Foundation of Liaoning Province (20170540471).

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Authors and Affiliations

  1. School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, China

    Yu Hu, Tiezheng Nie, Derong Shen, Yue Kou & Ge Yu

Authors
  1. Yu Hu
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  2. Tiezheng Nie
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  3. Derong Shen
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  4. Yue Kou
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  5. Ge Yu
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Corresponding author

Correspondence to Yu Hu.

Additional information

Yu Hu received his Bachelor Degree of Engineering and Master Degree of Computer Science from Northeastern University, China. He is currently a PhD candidate in Computer Software and Theory at NEU. His research interests include machine learning and the applications in bioinformatics.

Tiezheng Nie received his PhD Degree at Northeastern University, China. He is currently an assistant professor at the Department of Computer Science and Engineering. His research interests are related to database, data integration and data quality.

Derong Shen received her PhD Degree in Computer Science at Northeastern University (NEU), China. She is currently a professor at the Department of Computer Science and Engineering, NEU. Her research interests are related to distributed computing, data integration and knowledge base.

Yue Kou received her PhD Degree in Computer Science at Northeastern University (NEU), China. She is currently an assistant professor at the Department of Computer Science and Engineering, NEU. Her research interests include database theory, machine learning and software engineering.

Ge Yu received his PhD Degree in Information Engineering at Kyushu University, Japan. He is an experienced researcher. He now serves as head of the Department of Computer Science and Engineering, Northeastern University, China. His research interests include database theory.

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Hu, Y., Nie, T., Shen, D. et al. An integrated pipeline model for biomedical entity alignment. Front. Comput. Sci. 15, 153321 (2021). https://doi.org/10.1007/s11704-020-8426-4

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