Secondly, Building text categorization model, and training the model by a great many harmful information samples data.
第二、建立文本分类模型，使用大量的有害信息样本数据训练分类模型。
Experiment shows that the revised text categorization model meets the need of text categorization, and improves the performance of former one.
实验证明，改进后的文本分类模型适合于文本分类的需要，改善了原有分类器的性能。
This paper presents a text categorization model based on multilayered feedforward neutral network, and introduces the design and implementation of this model.
给出一种基于多层前馈神经网络的中文文本分类模型，介绍了该模型的设计和实现。
A multiclass text categorization model based on latent semantic analysis and support vector machine is researched and designed to enhance the accuracy of categorization.
为了提高文本分类的准确性，研究并设计了一个基于潜在语义分析和支持向量机的多类文本分类模型。
The experimental results show that the performance of text categorization model based on entropy is a relatively stable algorithm, and prove the effectiveness of the algorithm.
实验结果表明基于信息熵的文本分类模型是一种比较稳定的算法，证明了算法的有效性。
Finally, based on basic research of multi-class categorization of SVM, the text applies the theory to practice and analyzes a web text categorization model based on SVM network.
最后在完成基于SVM多类别分类的理论研究的基础上，将其理论应用于实践，构建了一个了基于SVM的网络文本分类模型。
The familiarity, embodiment, perceptibility and basic level categorization of the contents carried by the multimedia-interface are crucial for children to construct sound mental model.
界面源域中内容的熟知性、形体性、感知性和基本等级性是儿童对抽象概念构建一个清晰的心理模式的关键。
In the aspect of individual characteristics, we use the method of contrast and categorization separately and establish individual research model.
在个别性研究方面，本文分别运用了对比研究和范畴研究的方法，确立了种种个别性研究的模式。
This model depicts the knowledge structure and the relationship between knowledge in the conceptual level. It solves the problem of dynamic categorization of knowledge.
该模型在概念的层次上刻画学科领域的知识结构及知识之间的关系，解决了知识动态分类的问题。
This paper has put forward a function model and analysis framework for statistical categorization and designation.
本文建立了统计分组和指标设计的函数模型及分析框架；
The most important issue in text categorization is mathematical expression model of text data.
文本开类的沉要题纲非文本数据的数教外示模型。
Research on the key techniques and typical methods of text categorization are being done, and the method of text categorization based on word vector space model is presented in the dissertation.
本文对文本分类的关键技术及典型分类方法进行了研究，提出基于词向量空间模型的文本分类方法。
In the most categorization algorithms, the text or document is always represented using Vector Space Model.
纲后长数文本开类方式都非以背量空间模型为基本的。
It introduces the method of the text auto-categorization, briefly describes the vector space model expression, and finally gives training arithmetic and categorization arithmetic of the text.
本文介绍了文本自动分类的研究方法，文本的向量空间模型表示。并给出了文档的训练算法和分类算法。
There are four cognitive models of categorization: propositional model, image-schematic model, metaphoric model and metonymic model respectively.
范畴化的认知模型可归结为：命题模型、意象图式模型、隐喻模型以及转喻模型。
This paper proposes a visual words ambiguity analysis method based on text categorization. The codebook is generated by the BOW model.
为解决该问题，提出一种基于文本分类的视觉单词歧义性分析方法。
The de-categorization of "counterfeit" morpheme and the generalization of "X" morpheme play a key role in the process of mental solidification and construction of "Counterfeit X" word-model.
在经历心理固化，构建＂山寨X＂词语模过程中，＂山寨＂语素的去范畴化和＂X＂语素的泛化起关键作用。
This article first gives the definition and categorization of customer value, discusses customer potential value, and constructs a multivariate profit model for predicting customer potential value.
从客户价值的定义和划分入手，详细讨论了客户的潜在价值，建立了一个预测客户潜在价值的多变量概率单位模型；
This article first gives the definition and categorization of customer value, discusses customer potential value, and constructs a multivariate profit model for predicting customer potential value.
从客户价值的定义和划分入手，详细讨论了客户的潜在价值，建立了一个预测客户潜在价值的多变量概率单位模型；
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