And the process of Web usage mining was simply analyzed. Based on Web mining, personal recommendation algorithm was presented. Finally, a system structure of Web education based on the algorithm was put forward.

At the same time, the personalized recommendation algorithm that the paper used based on Web log mining be tested and the results prove that with high precision, and a certain degree of practical value.

同时，本文中采用的基于Web日志挖掘的个性化推荐算法，经测试结果证明，具有较高的查准率，有一定的实用价值。

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Research on the Personalized Recommendation Based on TOPSIS Method

基于TOPSIS算法的个性化推荐研究

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Web Personalization Recommendation Technologies in CtoC E-commerce Websites

CtoC电子商务站点中的Web个性化推荐技术

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The system architecture separates the offline process of data preparation and Web mining, and the online process of customizing Web pages based on a user's active session.

系统在结构上分为离线模块和在线模块，离线模块包括原始数据的预处理和挖掘算法的运行：在线模块使用个性化推荐引擎向客户提供个性化Web页面推荐。

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This framework mainly contained the functions of human-computer interaction, user interest learning, system data management, information search, agent collaboration and so on.

设计了一种基于Agent元搜索引擎的个性化推荐系统的框架，包含人机交互、用户兴趣学习、系统数据管理、信息搜索、多Agent协同等功能。

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Realization and Research on Community Monitoring& Personalized Recommendation System Based on E-Learning

基于E-Learning的社区监控及个性化推荐系统的实现

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The personalized recommender system as a important information filtration mean is a potential method to solve the problem of information overload currently.

个性化推荐系统（Recommender System）作为一种信息过滤的重要手段，是当前解决信息超载问题的非常有潜力的方法。

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It also introduces Web Log Mining on the concept and steps, describes personalized recommendation on the concept, classification, core technologies and procedures.

阐述了Web日志挖掘的概念和步骤，描述了个性化推荐的概念、分类、核心技术和步骤。

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If the past of the Internet is a popular search technology era, the future of the Internet will belong to personalized recommendation technology.

如果说过去的Internet是搜索技术大行其道的时代，那么未来的Internet将属于个性化推荐技术。

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With the rapid development of Internet and the online shopping system, the technology of personalized recommendation has become an important field gradually.

随着Internet和网上购物的迅猛发展，网上购物系统中的个性化推荐技术逐渐成为人们研究的一个重要领域。

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So, the implementation of web PRSs based on voting mechanism and technologies, is becoming a hot topic for researchers.

因而基于投票机制的Web个性化推荐系统以及技术的实现成为研究者热点关注的方向。

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Web personalized recommender systems anticipate the needs of web users and provide them with recommendations according to their navigation patterns.

Web个性化推荐系统根据用户的浏览模式预测用户需求，并向他们提供个性化的推荐服务。

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Personalized Recommendation Services has been considered as a typical method to deal with the problem of internet mass information.

个性化推荐是一种已经被公认的能够有效解决internet信息过载的方法。

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Web User Clustering and Personalized Recommendation Based on Mixtures of Hidden Markov Chain Models

基于混合隐Markov链浏览模型的WEB用户聚类与个性化推荐

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Research on Agent-Based Personalized Recommendation System

基于Agent的个性化推荐系统的研究

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A new approach of personalize recommendation uses agent technology and feedback mechanism

基于agent技术和反馈机制的个性化推荐方法研究与设计

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A personal recommendation algorithm based on Web mining

基于Web挖掘的一种个性化推荐算法

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Web data mining used in the personalized recommendation service

Web数据挖掘在个性化推荐服务的应用

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Web mining is one of the key technologies of web personal recommendation.

Web挖掘是实现Web个性化推荐的关键技术之一。

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Research of Personalized Recommendation System Based on Web Usage Learning

基于WEB使用挖掘的个性化推荐系统的研究

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