Drug-Drug Relationship Extraction Based on Capsule Networks
LIU Ningning1, JU Shenggen1, XIONG Xi2,WANG Jingyan1,ZHANG Rui1
1.School of Computer Science, Sichuan University,Chengdu,Sichuan 610065,China; 2.School of Cybersecurity, Chengdu University of Information Technology, Chengdu,Sichuan 610225,China
Abstract：Drug-Drug interaction refers to the inhibition or promotion between drugs. To improve the current Drug-Drug interaction relationship extraction model’s performance in the long sentences, this paper proposes a capsule network extraction model that combines the shortest dependent path. The approach first detects the shortest dependent path between two drugs in the parse of the original sentence, then applies the Bi-LSTM to obtain the embedding of the original sentence and the shortest dependent path. The embedding are them put into the capsule network, in which the dynamic routing mechanism could dynamically determine the amount of information transmitted and preserve the high-level feature information. The experimental results on the DDIExtraction2013 show that the proposed achieved 1.17% relative increase in F1 value compared with the current best approaches.
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2020, Vol. 34 
