1) word co occurrence
单词同现
1.
The approach has the virtue of the demand for a small training set and it can avoid the problems in traditional methods based on word co occurrence, such as the demand for a large corpus, sparse data, etc .
这一方法只要较少的学习例子 ,可以避免传统的基于单词同现的方法中需要大量的语料库及数据稀少等问
2) Words co-occurrence
词同现
1.
Based on the analysis of words frequency and position distribution features,an automatic summarization model(Automatic Summarization Model Based on Words co-occurrence and Position Features: ASMWF)was proposed.
在利用统计方法对文摘中词频特征和词位置分布特征进行分析的基础上,提出增加词同现特征用于自动文摘系统的新方法。
3) word co-occurrence
词同现频率
1.
Text feature description based on word co-occurrence;
基于词同现频率的文本特征描述
4) Single-syllables
单音同义词
5) monosemous
单义同义词
1.
The monosemous lexical relatives substitution of target words have been proposed to acquire WSD corpus from the Web automatically.
有人提出了利用目标词的单义同义词在生语料中自动获取词义消歧语料的方法,然而,在某些上下文当中,用目标词替换这些单义的同义词并不合适,从而带来噪声。
补充资料：非现现
【非现现】
谓如来三昧，寂然不动，为众生故，于非应中随感而应。犹如明镜，无心现物，而像对即现，是名非现现。
谓如来三昧，寂然不动，为众生故，于非应中随感而应。犹如明镜，无心现物，而像对即现，是名非现现。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条