The method is based on vector space model and process neural network.
同时介绍了空间矢量调制的算法。
At last, we also employ the classic Vector Space Model to classify the documents.
最后，我们使用经典的向量空间模型来实现文档的分配。
This paper USES the classical vector space model for text classification Web page.
采用经典的向量空间模型对网页文本进行分类。
In information retrieval, vector space model is one of significant mathematics tools.
在信息检索中，向量空间模型是最有效的数学工具之一。
A new approach of email classification based on the concept vector space model was proposed.
提出了一个基于概念向量空间模型的电子邮件分类方法。
Firstly character words of training documents are extracted, vector space model is constructed.
首先提取出文本训练集的特征词，建立特征向量空间模型。
We Construct a system of Chinese automatic summarization based on conceptual vector space model.
开发了一个基于概念向量空间模型的中文自动文摘系统。
Comparing with the traditional vector space model, this new model is faster for information retrieval.
与向量空间模型相比，该模型的检索速度明显提高。
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。
The user model is expressed in form of vector space model. It's built using centroid-based classification method.
基于向量空间模型表示用户模型，采用重心向量分类算法建立用户模型。
Vector space model is constructed with HTML tag weights, which offset the distribution differences of text terms.
结合HTML标记权重信息建立向量空间模型，弥补了特征项在文本集合中分布的差异。
A classification method based on fuzzy vector space model and radial basis function network is presented in this paper.
文本提出了一种基于模糊向量空间模型和径向基函数网络的分类方法。
The first algorithm is based on random walk with restart model, which modifies the model to support vector space model.
基于重启型随机游走的图上关键字搜索算法，在重启型随机游走模型的基础上加入了向量空间模型。
There are disadvantages of traditional vector space model in computational complexity, query efficiency and intelligence.
传统向量空间模型在计算复杂度、查询性能、智能性方面存在种种缺陷。
This article discussed the algorithms of literature filtering based on vector space model (VSM) and other improved models.
本文从理论上探讨了向量空间模型及其改进模型在专题文献过滤中的相关算法。
Based on tradition filtering algorithm, an adaptive filtering algorithm based on vector space model is proposed in the paper.
在传统过滤算法的基础上，本文提出一种基于向量空间模型的自适应过滤算法。
In addition, a text classification system based on Vector Space Model is studied and a new method for calculating word weight is proposed.
此外，本文还研究了基于向量空间模型的自动文本分类方法，提出了一个新的词权重计算方法，该方法有效提高了分类精度。
At present there are the Boolean model, the vector space model, the probabilistic model and distorted model of the above three classic models.
目前已有的检索模型有布尔模型、向量模型、概率模型以及以上三个经典模型的变形模型。
Aimed at the problems of document automatic classification, a classification method is proposed based on fuzzy vector space model and RBF network.
针对文本自动分类问题，提出了一种基于模糊向量空间模型和径向基函数网络的分类方法。
Internet resource search for specific subject websites was realized using a hybrid vector space model developed to describe website subject features.
为了实现面向特定领域网站的网络资源搜索，提出了一种描述网站主题特征的混合向量空间模型。
In designing web Classifier, this thesis makes use of Vector Space Model to represent the web text, which improves the performance of Bayes Classifier.
在文本分类器的设计中，用传统信息检索的空间向量模型改进了朴素贝叶斯分类器，提高了它的分类精度。
This paper gives an analysis of these problems and provides some corresponding method for improvement. Finally, an improved vector space model is presented.
本文就这些问题给予分析并给出了相应的改进方法，最后构建了一个改进后的向量空间模型。
A cell classify system based on vector space model was introduced and a fast fuzzy based algorithm for recognizing capacity and curve of battery was proposed.
介绍了一个建立在向量空间模型上的电池分类系统，提出了一个基于模糊决策的快速完成识别电池容量和曲线一致性的计算方法。
This paper uses the Vector Space Model to express the features of event description segment and calculate the importance of feature words in different classes.
使用向量空间模型来表示事件描述片段的特征，并分类计算特征词的重要度，最后对文本中的事件片段进行定位和分类。
This paper discusses different Vector Space Model(VSM)-based clustering algorithms and presents an improved text clustering algorithm——Level-Panel(LP)algorithm.
该文探讨了基于向量空间模型的文本聚类方法，提出 了一种文本聚类的改进算法——LP 算法。
This paper introduces a text filtering system merging topic classification based on vector space model and sentiment classification based on support vector machine.
该文介绍了一种文本过滤算法，该算法把基于空间向量模型的主题分类算法与基于支持向量机文本态度分类结合起来。
Therefore, by some analysis, the combination of classification based on vector space model and which based on semantic is one of the best solutions to this problem.
本文通过认真分析，认为在基于向量空间模型的分类方法中可以适当地借鉴基于语义的分类方法中的权重设置方法。
Most of the content-based filtering algorithms are based on vector space model, of which Naive Bayes algorithm and K-Nearest Neighbor (KNN) algorithm are widely used.
基于内容的过滤算法大多数是基于向量空间模型的算法，其中广泛使用的是朴素贝叶斯算法和K最近邻（KNN）算法。
Most of the content-based filtering algorithms are based on vector space model, of which Naive Bayes algorithm and K-Nearest Neighbor (KNN) algorithm are widely used.
基于内容的过滤算法大多数是基于向量空间模型的算法，其中广泛使用的是朴素贝叶斯算法和K最近邻（KNN）算法。
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