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Extracting and Sharing Knowledge from Medical Texts

Keywords: Encyclopedia of China,knowledge acquisition,high-level conceptual lanhuage,knowledge compilation,IO-model
人工智能
,医学文本知识,数据采集,知识共享

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Abstract:

In recent years, we have been developing a new framework for acquiring medical knowledge from Encyclopedic texts. This framework consists of three major parts. The first part is an extended high-level conceptual language (called HLCL 1.1) for use by knowledge engineers to formalize knowledge texts in an encyclopedia. The other part is an HLCL 1.1 compiler for parsing and analyzing the formalized texts into knowledge models. The third part is a set of domain-specific ontologies for sharing knowledge. This work is supported by a grant from the Chinese Academy of Science (No.#2000-4010), and a grant from National Natural Science Foundation of China (No.#20010010-A), a grant from the Ministry of Science and Technology (#0221CCA03000). CAO Cungen is a professor of artificial intelligence. His main interests include knowledge acquisition and knowledge-based systems.

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