Abstract
Due to the diversity of natural language in Chinese electronic medical records, it is usually hard for traditional retrieval methods to provide ideal results. On this condition, this paper proposes a retrieval method for Chinese EMR based on semantic knowledge map. Through natural language processing and semantic analysis, we can build connections for medical knowledge, and organize all the entities into a visual knowledge map. After that, a novel retrieval method based on semantic knowledge map is proposed, which focuses on node connection of documents and terms. Through semantic extension and intention spread, the improved retrieval results are returned, and the results are reordered by correlation. Compared with general methods, this method can significantly improve the accuracy of Chinese EMR text retrieval and optimize the ranking strategy of retrieval results.
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