基于词性分析和领域知识的deep web语义标注

Deep Web Semantic Annotation Method Based on Chinese Part-of-Speech and Domain Knowledge

该构式中的S指主语，X指谓词性短语和主谓短语。

S refers to subject, X refers to predicative phrase and subject& object phrase.

分词和词性标注模块采用了最大词长匹配算法，句法分析模块采用了改进的Chart算法。

They have adopted the Maximum Match based approach algorithms and improved Chart algorithm separately.

基于词性的文本挖掘算法在IDS日志中的应用

A text mining Algorithm Based on part of speech used in IDS logs

采用词汇判断任务和记录ERP的方法，探讨了名词与动词之间的差异以及词汇的具体性对这种词性效应的影响。

An experiment was conducted to examine the difference between noun and verb words using ERP measurements and lexical decision task.

基于HMM的藏语语料库词性自动标注研究

Researches of Part of Speech Tagging for Tibetan Texts Based on Hidden Markov Model

运用语料库研究方法，以英语中两个常用词TOTAL和PLEASE为例，分析了中国学生在写作中使用多词性词时的一些特征。

Taking two commonly-used words "TOTAL" and "PLEASE" as examples, this paper studies some of the features Chinese students exhibit with the use of polycategorials.

现代汉语NV式状中偏正短语能够占据谓语的位置，其中的V仍保留动词特征，整个短语是谓词性的。

In modern Chinese, NV phrase with N as adverbial can function as predicate.

SSD模型及其在词性标注中的应用

Symbol-and-Statistics Decoding Model and Its Application in POS Tagging

N的V结构中的V仍然是谓词性成分，一般来说是动作性较弱、及物性较低的谓词。

V is still a predicative component in the N de V structure, in general the V in this structure is always low in transitivity scale. 3.

用HMM实现日文词性标注的训练和标注过程，并对稀疏数据进行平滑。

As for Japanese Part-of-Speech Tagging, the thesis adopts HMM to train the model, and uses data sparseness smoothing strategy.

通过动词与其动趋式短语的功能差异比较，可以看出汉语中X词和X词性短语在功能上是有差异的。

By comparing the functional difference of verb and its verb-trending phrase, we conclude that the function of word X in Chinese and that of its syntactical and morphological phrase are different.

HNC理论的五元组与词性

The Quintuple of HNC theory and part of speech