Abstract
Currently, knowledge graphs can be used to better query complex related information, understand user intentions from the semantic level, and improve search quality. With the increase in cross-lingual medical data recently, the construction of cross-lingual knowledge graph in the medical domain is urged. Meanwhile, there also exist many challenges due to the specific features in the medical area: (1) the scarcity of Chinese knowledge and the inner relations within the entities in existing open source cross-lingual knowledge bases; (2) the scarcity of prior knowledge defined by medical experts; (3) the availability of Electronic Medical Records (EMRs) and (4) the inconsistent semantic rules in different languages. To overcome these limitations, we propose CLMed platform which can be used in constructing the disease-specific, cross-lingual medical knowledge graphs from multiple sources. This platform provides several toolsets to process the cross-lingual data. Meanwhile, based on this platform, we generate a large scale, cross-lingual medical knowledge graph named CLKG.
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Acknowledgments
This work was supported by NSFC (91646202), National Key R&D Program of China (2018YFB1404400, 2018YFB1402700).
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Sheng, M. et al. (2019). CLMed: A Cross-lingual Knowledge Graph Framework for Cardiovascular Diseases. In: Ni, W., Wang, X., Song, W., Li, Y. (eds) Web Information Systems and Applications. WISA 2019. Lecture Notes in Computer Science(), vol 11817. Springer, Cham. https://doi.org/10.1007/978-3-030-30952-7_51
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DOI: https://doi.org/10.1007/978-3-030-30952-7_51
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