word sense
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英汉解释
例句
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。
Word sense disambiguation is one of the difficult problems in natural language processing.
词义消歧是自然语言处理中的难题之一。
Word sense tagging is one of the most difficult problem in natural language processing.
词义标注是自然语言处理的难题之一。
The range of polysemous words as the object of the computer automatic word sense disambiguation is delimited.
先界定了作为计算机自动词义消歧对象的多义词的范围；
This paper investigates their application effect on Chinese Word Sense Disambiguation (WSD) by experiments.
本文通过实验考察了这两种网络模型在汉语词义消歧上的应用效果。
The POS and word sense disambiguation approaches based on individual rules have been experienced in non-lexical paralleled parallel corpus.
第三，在未经词汇对齐的平行语料中，实践了基于个性规则的词性、词义消歧方法。
The elaborated context cue is also helpful, indicating contextual information as useful in resolving word sense ambiguity.
具体阐述的语境提示也是有效的，表明语境信息在解决词义的歧义方面也是有效的。
thee expression of multiple syntactic forms: a single word sense can have multiple syntactic realization.
同一个意义可能会有多个不同的句法表现。
Bayesian network is simple, effective and easy constructed for classifying word sense.
贝叶斯网络用于词义分类简单高效，模型容易构造；
The rate of correct word sense disambiguation is over 98 % in the closed test, and over 96% in the open test.
词义消歧的精确率，封闭测试高达98%以上，开放测试高达96%以上。
A word sense disambiguation method based on semantic graph structure was presented.
提出了一种基于语义网络结构的词义消歧方法。
Therefor, it is necessary to do the professional studies on word sense for MT.
为此，我们有必要为机器翻译这个特定的自然语言处理领域做专门的语义研究。
The Function of the Word Sense in Sentence Understanding
词的具体意义对句子意思理解的影响
HowNet; Similarity of concept; Word sense disambiguation; Ratio of the amount of information; Sentences semantic similarity;
知网；概念相似度；词语消歧；信息量比；句子语义相似度；
Word Sense Disambiguation of Adjectives Using Probabilistic Networks
使用概率网络的形容词的词义消岐
Software platform oriented to Chinese word sense automatic tagging research
面向汉语词义自动标注研究的软件平台开发
Coarse-Grained Word Sense Disambiguation Using Features Described in the Lexicon
基于词典属性特征的粗粒度词义消歧
The Research Progress of Statistical Word Sense Disambiguation
统计词义消歧的研究进展
The Model of Word Sense Disambiguation Combining Statistics and BP Neural Networks
统计与神经网络相结合的词义消歧模型
Word Sense Disambiguation with Semantic Graph Structure
语义网络结构下的词义消歧
Unsupervised Chinese Word Sense Disambiguation Based on Dependency Grammar Analysis and Bayesian Network
基于依存分析和贝叶斯网络的无指导汉语词义消歧
Word Sense Disambiguation of Spoken Chinese Using Neural Network
基于神经网络的汉语口语多义选择
The State-of-the-Art and Future Aspects of Word Sense Disambiguation
词义消歧研究的现状与发展方向
Computational Method for Word Sense Evolution
词义演化的计算方法
Word Sense Tagging in Chinese- English Parallel Corpora
汉英双语平行语料库的词义标注
New Chinese Word Sense Disambiguation Method
一种新的汉语词义消歧方法
Implement a full- text automatic system for word sense tagging
一个全文词义自动标注系统的实现
Word Sense Disambiguation Based on Dependency Relationship Analysis and Bayes Model
基于依存分析改进贝叶斯模型的词义消歧
An Improved Chinese Word Sense Disambiguation Method Based on Primitive Co-Occurrence Data
改进的基于义原同现频率的汉语词义排歧方法
Full-words Automatic Word Sense Tagging Based on Unsupervised Learning Algorithm
基于无指导机器学习的全文词义自动标注方法
Solution Strategies for Word Sense Problems Based on Vector Space Model and Maximum Entropy Model
基于矢量空间模型和最大熵模型的词义问题解决策略
Unsupervised word sense tagging method based on transformation rules
基于转换的无指导词义标注方法
Unsupervised approach to word sense disambiguation based on vector space model
基于向量空间模型的无导词义消歧
A model of Chinese word sense disambiguation based on combining rule and statistics method
规则与统计相结合的汉语词义消歧模型
A Chinese Word Sense Disambiguation System Based on Primitive CO- Occurrence Data
基于义原同现频率的汉语词义排歧系统
Using the BP neural networks to Chinese word sense disambiguation
利用BP神经网络的中文词义消歧模型
Word Sense Disambiguation Based on Multi-Classifier Decision
基于多分类器决策的词义消歧方法
Method of word sense disambiguation based on bayes and machine readable dictionary
一种基于贝叶斯分类与机读词典的多义词排歧方法
Chinese word sense disambiguation based on extension theory
基于可拓学理论的汉语词义消歧
An introduction of word sense disambiguation based on Bayers model
浅谈基于改进贝叶斯模型的词义消歧方法
