| 1. | Annotation of texts based on how - net
基于知网的文本标注 |
| 2. | The research on reduced feature dimension based on hownet similarity computing
基于知网语义相似度计算的特征降维方法研究 |
| 3. | We choose the interrogative words , syntax structure , question focus words and their first sememes as classification feature
该方法以问题的疑问词、句法结构、疑问意向词、疑问意向词在知网中的首义原作为分类特征。 |
| 4. | And last , it mainly lays emphasis on the research of chinese text clustering . it designs a concept clustering algorithm based on the hownet
然后,针对中文文本的聚类,本文设计了以知网为背景知识的概念聚类算法。 |
| 5. | First we put forward the general idea about this method and give a brief introduce to its semantic knowledge resource - the hownet dictionary
本文首先提出了这种方法的总体思路，并对其语义知识资源《知网》作了简要的介绍。 |
| 6. | In this paper , we present a new method on feature extraction which uses hownet as semantic resource , and use maximum entropy model to realize it
本文提出了一种使用知网作为语义资源选取分类特征，并使用最大熵模型进行分类的新方法。 |
| 7. | The experiment result show that the first sememes in hownet can express the main meaning of the question focus words , it can be as an important feature
实验结果表明，在知网中选取的首义原能很好的表达问题焦点词的语义信息，可作为问题分类的一个主要特征。 |
| 8. | Chapter two puts forward the general idea about our main idea of the disambiguation model . then it gives a brief introduce to its semantic resource - the hownet dictionary
第二章介绍了排歧模型的总体思想，并简要介绍了《知网》 、分析规则、中间语言等一些必要知识。 |
| 9. | In this chapter , the automatic algorithm for mapping wordnet senses to hownet concepts and the algorithm used to acquire fuzzy semantic patterns from examples are both described in detail
其中着重介绍了从wordnet到知网的词义映射算法、模糊语义模式自动训练算法等内容。 |
| 10. | In this paper , the representation , acquirement and application of the construction of chinese phrase were investigated systematically . hownet is used as main semantic resource
本文以《知网》为主要语义知识源，对汉语短语构造的语义规律的表示、获取以及应用作了系统的研究。 |
