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过滤模板
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  filtering profiles
    Techniques of improving filtering profiles in content filtering
    内容过滤中过滤模板的改进技术研究
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  filtering profiles
In our TREC-8 routing experiments, we employed a collaborative (or social) filtering algorithm, based on latent semantic indexing which highlights common term usage patterns among groups of filtering profiles.
      
Like ranking profiles, filtering profiles may also be specified by either document users or providers.
      
The database tables in the schema implement the tables for representing ranking or filtering profiles described in Section 4 and 5.
      
The options listed in the selection field are all the ranking or filtering profiles defined in the system.
      


Content filtering in network security need seek a balance between the filtering precision and instantaneity. This paper constructs the structure of content filtering system that can implement content filtering function. And, we put forwards a new machine learning method used as improving filtering profiles. We can prove by Markov model that this method can ensure the initial filtering profiles will converge gradually at authentic profiles. So, the filtering precision will be constantly increased.

网络安全中的内容过滤需要在过滤精度与实时性之间寻求平衡,本文首先建立了内容过滤系统的体系结构,它能够实现内容过滤功能。在此基础上,提出了一种对过滤模板进行改进的新的机器学习方法,利用马尔可夫模型可证明此方法能保证初始过滤模板在学习过程中逐渐收敛于真实模板,从而不断提高过滤精度。

nformation filtering is the procedure of retrieving documents relevant to the requirements of users through scouting information fountains.A information filtering system was given based on vector space model.This system is composed of two phases of training and adaptive filtering.During the training phase,feature selection and pseudo feedback were used to select the initial filtering profiles and thresholds.During the filtering phase,user feedback was utilized to modify the profiles and thresholds adaptively.The...

nformation filtering is the procedure of retrieving documents relevant to the requirements of users through scouting information fountains.A information filtering system was given based on vector space model.This system is composed of two phases of training and adaptive filtering.During the training phase,feature selection and pseudo feedback were used to select the initial filtering profiles and thresholds.During the filtering phase,user feedback was utilized to modify the profiles and thresholds adaptively.The evaluations and results were given.

信息过滤是指通过监控信息源以找到满足用户需求的信息的过程。详细地论述了基于向量空间模型的信息过滤系统,系统由训练和自适应过滤两个阶段组成,在训练阶段,通过主题处理和特征抽取建立初始的过滤模板,设置初始阈值;在过滤阶段,则根据用户的反馈信息自适应地调整模板和阈值,最后给出了评估方法和实验结果。

This paper introduces a new algorithm of text representation,which applies in Web document information filtering system.Compared with the traditional VSM,such an improved algorithm based on VSM makes more rapid filtering speed and higher filtering precision.This algorithm straight picks out attribute from attribute aggregate of filtering template,just disposes of the place where this attribute appeared in Web document.Then it gives different coefficient of weighting according to Web label which attribute perched...

This paper introduces a new algorithm of text representation,which applies in Web document information filtering system.Compared with the traditional VSM,such an improved algorithm based on VSM makes more rapid filtering speed and higher filtering precision.This algorithm straight picks out attribute from attribute aggregate of filtering template,just disposes of the place where this attribute appeared in Web document.Then it gives different coefficient of weighting according to Web label which attribute perched on,and gets more exact weightiness of attribute.Finally it finds Web document representation model from the above result.

介绍了一种新的文本表示算法,应用在网页文本过滤系统中。比起传统的向量空间模型,这种建立在其上的改进算法有更快的过滤速度和更高的过滤精度。该算法直接从过滤模板的特征集中取出词条,只在网页文本出现该词的地方进行精确处理。根据特征项所在的网页标签,赋予不同的权值系数,以准确定义特征词在文中的重要程度,最后建立该网页的文本表示模型。

 
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