A joint model for question-answering over Traditional Chinese Medicine
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Traditional Chinese Medicine (TCM) has been around for over 2000 years and it's a significant part of Chinese cultural heritage. The theoretical framework of TCM is unique and with rich of content, which contains the complex relationships between disease and medicine and has formed a unique system to diagnose and cure illness. Research on question-answering (QA) over TCM is significant for Chinese NLP and representative, because the resources of TCM are mostly Chinese-based. The general strategies for QA are pipeline, includes Natural Language Processing (NLP) for original questions and structural query process. However, noises are easily introduced and information contained in the original questions may loss during these two separate procedures. In this paper we present a novel joint model for QA over TCM, which unites these two procedures into a uniform framework, together with Wikipedia alignment. The results of our evaluation with 100 benchmark queries demonstrate the value of our approach.Keywords:
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