Improve Chinese Clinical Named Entity Recognition Performance by Using the Graphical and Phonetic Feature
Yifei Wang, Sophia Ananiadou, Junrichi Tsujii · 2018
Since Chinese language is quite different with English language, the machine cannot simply get the graphical and phonetic information form Chinese characters. Recent research on Chinese word embedding tries to use graphical information as subword. This paper uses both graphical and phonetic features to improve the performance of Chinese Clinical Named Entity Recognition. This research conducts and reports on an experiment performed to prove that the use of primary radical and pinyin can improve the performance of Clinical Named Entity Recognition and get the F-measure of 0.712.