车超,滕弘飞,. 伪实例与人工标注实例相结合的词义消歧方法[J]. 中文信息学报, 2009, 23(6): 31-39.
CHE Chao, TENG Hongfei,. Combining Pseudo-Samples and Manually-Tagged Samples for Word Sense Disambiguation. , 2009, 23(6): 31-39.
Combining Pseudo-Samples and Manually-Tagged Samples for Word Sense Disambiguation
CHE Chao1, TENG Hongfei1,2
1. Department of Compute Science & Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China; 2. School of Mechanical Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China
Abstract：The corpus-based method for word sense disambiguation (WSD) suffers from “knowledge acquisition bottleneck” problem. The automatic lexical sample acquisition method based on equivalent pseudo-words (EPs) is an effective way to solve of this problem. However, some pseudo-samples collected by EPs have low quality and the EPs can not be acquired when the ambiguous word has few monosemous synonyms. This paper proposes a WSD method combining pseudo-samples and man-acquired samples. The method calculates the sentence similarity with the context of the ambiguous word to remove pseudo-samples with low quality. Moreover, the method utilizes the manually-tagged corpus to get the sense distribution probability and provide samples for the ambiguous words that have little monosemous synonym. Our method achieves an average F-measure of 0.79 through the WSD experiments performed on Senseval-3 Chinese lexical sample task. Key words computer application; Chinese information processing; word sense disambiguation; HowNet; equivalent pseudo-words; Bayesian classifier; automatic sample acquisition;
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