Word sense disambiguation (WSD) plays an important role in many areas of natural language processing such as machine translation, information retrieval, sentence analysis, speech recognition.
词义排歧在机器翻译、信息检索、句子分析和语音识别等许多领域有重要的作用。
Using pseudowords we can overcome data sparseness problem in supervised WSD and fully verify the experimental effect of word sense classifier.
使用伪词可以避免有指导的词义消歧方法中的数据稀疏问题,充分验证词义分类器的实验效果。
Word Sense Disambiguation (WSD) has always been a difficult and hot points in natural language processing.
词义消歧是自然然语言处理中的一个难点和热点问题。
应用推荐