Patent AU-2020104254-A4 (AU)
Title: Healthcare question answering (qa) method and system based on contextualized language model and knowledge embedding
Inventor: WANG XIAOLI
IPC: G06F40/30
Filed: 2020-12-23
Granted: 2021-03-11
Abstract: The present disclosure discloses a healthcare question answering (QA) method and system 
based on a contextualized language model and knowledge embedding. The method includes: 
acquiring a healthcare question and a candidate healthcare answer in a healthcare answer database; 
using a trained contextualized language model to generate contextualized embedding of the 
healthcare question and contextualized embedding of the candidate healthcare answer; using a 
trained knowledge representation model to generate knowledge embedding of the healthcare 
question and knowledge embedding of the candidate healthcare answer; fusing the contextualized 
embedding and knowledge embedding of the healthcare question to obtain a feature representation 
of the healthcare question; fusing the contextualized embedding and knowledge embedding of the 
candidate healthcare answer to obtain a feature representation of the candidate healthcare answer; 
calculating a correlation of the candidate healthcare answer with the healthcare question according 
to the feature representation of the healthcare question and the feature representation of the 
candidate healthcare answer; and determining a healthcare answer to the healthcare question 
according to correlations of various candidate healthcare answers in the healthcare answer database 
with the healthcare question. The present disclosure can realize effective retrieval of answers and 
improve retrieval efficiency.  
13
DRAWINGS 
101 
Acquire a healthcare question 
102 
Use a trained contextualized language model to extract contextualized embedding of the10 
healthcare question 
103 
Use a trained knowledge representation model to extract knowledge embedding of the healthcare 
question 
104 
Fuse the contextualized embedding of the healthcare question and the knowledge embedding of 
the healthcare question to obtain a feature representation of the healthcare question 
105 
Acquire a healthcare answer in a healthcare answer database and mark the healthcare answer as a 
candidate healthcare answer 
106 
Use the trained contextualized language model to extract contextualized embedding of the 
candidate healthcare answer 
1 107 
Use the trained knowledge representation model to extract knowledge embedding of the 
candidate healthcare answer 
1 108 
Fuse the contextuaized embedding ot the candidate healthcare answer and the knowledge108 
embedding of the candidate healthcare answer to obtain a feature representation of the candidate 
healthcare answer 
109 
Calculate a correlation ot the candidate healthcare answer with the healthcare question accordmg 
to the feature representation of the healthcare question and the feature representation of the 
candidate healthcare answer 
No 
Calculate correlations of all 
candidate healthcare answers in the healthcare 
answer database with the 
ealthcare questio 
Yes 110 
Determine a healthcare answer to the healthcare question according to the correlations 
FIG. 1 
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