Automatic Word Sense Disambiguation Method Based on Wikipedia
Minglu Li · Jisuanji gongcheng · 2009
Most traditional Word Sense Disambiguation(WSD) method is just based on contextual information, often results in inaccurate output.A multi-level unsupervised automatic WSD method which works efficiently is promoted.This method utilizes the rich semantic information extracted from online Wikipedia, makes a linear fusion of contextual information, background knowledge and semantic information, uses logistic regression algorithm to learn the weight of each feature, and selects the one with the maximum combined value as correct meaning.Experimental result on SENSEVAL dataset shows an average precision of 85.50%, therefore validates the feasibility and effectiveness of this method.