Word Sense Disambiguation Model with a Cache-Like Memory Module  

作　　者：LIN Qian LIU Xin XIN Chunlei ZHANG Haiying ZENG Hualin ZHANG Tonghui SU Jinsong 林倩;刘鑫;辛春蕾;张海英;曾华琳;张同辉;苏劲松(School of Informatics,Xiamen University,Xiamen 361005,China)

机构地区：[1]School of Informatics,Xiamen University,Xiamen 361005,China

出　　处：《Journal of Donghua University(English Edition)》2021年第4期333-340,共8页东华大学学报（英文版）

摘　　要：Word sense disambiguation(WSD),identifying the specific sense of the target word given its context,is a fundamental task in natural language processing.Recently,researchers have shown promising results using long short term memory(LSTM),which is able to better capture sequential and syntactic features of text.However,this method neglects the dependencies among instances,such as their context semantic similarities.To solve this problem,we proposed a novel WSD model by introducing a cache-like memory module to capture the semantic dependencies among instances for WSD.Extensive evaluations on standard datasets demonstrate the superiority of the proposed model over various baselines.

关 键 词：word sense disambiguation(WSD) memory module semantic dependencies 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]