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个性化信息过滤
相关语句
  personalized information filtering
     Design and Implementation of Agent-Based Personalized Information Filtering System
     基于Agent的个性化信息过滤系统的设计与实现
短句来源
     Research on Personalized Information Filtering System in Web-based Learning
     网络学习的个性化信息过滤系统研究
短句来源
     With the requirement of user's specific information service,a framework of personalized information filtering system,based on Agent,is proposed and implemented in this paper.
     针对用户个性化服务的特定需求,文中提出了一种基于Agent的个性化信息过滤系统的设计思想及其实现过程。
短句来源
  personal information filtering
     Personal Information Filtering Technology with Time Factor
     加入时间因素的个性化信息过滤技术
短句来源
     Technology and Implementation Method on Personal Information Filtering Based on Agent
     基于Agent的个性化信息过滤技术与实现方法
     Describes a personal information filtering technology with time factor.
     提出一种加入时间因素的个性化信息过滤技术.
短句来源
  individualized information filtering
     Research on the Models of the Individualized Information Filtering System
     个性化信息过滤系统模型研究
短句来源
     To meet this need,this paper puts forward a model of the individualized information filtering system,introduces its framework,and elaborates its key technologies.
     针对这种需要,提出了一种个性化信息过滤系统的模型,介绍了其总体结构,并深入分析了其关键技术。
短句来源
  “个性化信息过滤”译为未确定词的双语例句
     Research and Design of Personalized Content Filtering System
     基于内容的个性化信息过滤系统的研究与设计
短句来源
     A Study on the Personalized Agent-based Information Filterling Technology and Its Implementation
     基于Agent的个性化信息过滤技术的研究及实现
短句来源
     Information filtering technique based on term-frequency
     基于词频统计的个性化信息过滤技术
短句来源
     In the personalized learning system, the difficulty of design and implementation includes two aspects: discovering personality from user learning behavior, retrieval among or filtering from learning objects and then composing personalized instruction.
     本文研究的个性化信息过滤技术用于个性化网络学习环境,技术实现的难点体现在两个方面:用户学习行为个性识别和学习对象的个性化检索与发送。
短句来源
     Hence, personalized information service is implemented.
     系统既可以根据用户喜好进行个性化信息过滤
短句来源
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  personalized information filtering
It is especially helpful for the design of personalized querying and retrieval system, and personalized information filtering and delivery.
      


This paper discusses the implementation of a personalized intelligent agent that performs information filtering on Internet. The agent can follow user interests dynamically, and filter information to determine which is of interest to the user when he inquires. This is done by converting documents into their Vector Space Model and performing BP neural network to learn user interests.

论述了一个Internet网上个性化信息过滤智能体的实现。它采用向量空间模型[3] 作为文档表示的基础 ,通过抽取用户浏览网页的特征 ,使用BP神经网络来学习和跟踪用户的兴趣 ,从而动态了解用户的浏览行为 ,并在用户查询时能有效地过滤出用户感兴趣的信息。

With the exponential growth of World Wide Web, it becomes more and more time and energy consuming for users to find what they're interested in It leads to a clear demand for personalized services, which can provide different users with different services User modeling is the key technology in implementing personalized services Conventional user modeling methods with both positive and negative examples will either interfere users' normal browsing or bring in noises A user modeling method without negative...

With the exponential growth of World Wide Web, it becomes more and more time and energy consuming for users to find what they're interested in It leads to a clear demand for personalized services, which can provide different users with different services User modeling is the key technology in implementing personalized services Conventional user modeling methods with both positive and negative examples will either interfere users' normal browsing or bring in noises A user modeling method without negative examples is presented A hybrid of genetic algorithms and kNN classifier are utilized to search the words describing users' interests The method is applied in personalized information filtering The experiments show that the filtering ratio and precision can be 73 91% and 94 44% respectively, which demonstrates that our user modeling method is feasible and efficient

随着WWW信息的快速增长 ,查找用户感兴趣的信息变得越来越耗时耗力。个性化服务能为不同的用户提供有针对性的服务 ,日益受到研究者的重视。用户建模是实现个性化服务的关键技术。传统的需要正、反例集作为训练例集的用户建模方法容易干扰用户的正常浏览 ,或者由于推断失误而引入噪声。基于遗传算法和k近邻方法提出了一种无需反例集的用户建模方法 ,该方法被应用于个性化信息过滤中。实验结果表明 ,基于无需反例集的用户建模方法的信息过滤算法可以达到 73 91%的过滤率和 94 4 4 %的过滤精度。无需反例集的用户建模方法是一种可行、高效的用户建模方法

This paper introduces the personal information filtering technology,illustrates its basic principle,builds personal need model system and uses categorized algorithm,finally summarizes exiting problems.

提出了个性化信息过滤技术 ,并对其基本原理进行了阐述 ;构建了用户个性化模式 ,给出了用户分类算法。最后 ,对当前存在的问题进行了总结。

 
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