This paper describes the realization process of the personalized information recommendation in theory.
本文从实现的原理上对该个性化信息推荐方式进行了理论探讨。
The proposed idea and technique can also be used for other personalized information recommendation systems on the Internet.
所述的设计思想和技术也适用于其它互联网个性化信息自动推荐系统。
On the ground of above work, we designed and implemented a personalized information recommendation system of interest-based model.
在上述工作的基础上，设计并实现了基于兴趣模型的个性化信息推荐系统。
The research of personalized Active information Service has made a big progress during these years, the most important of which is personalized information recommendation.
近年来，个性化主动信息服务的研究取得了很大的进展。而在个性化主动信息服务中最重要的服务就是个性化信息推荐。
Finally, studies on personalized information recommendation based on social tagging are analyzed, and find matrix, clustering and network analysis are three primarily methods.
最后，分析了社会化标注中个性化信息推荐的研究，发现借助矩阵、聚类和网络的分析是三种主要思路。
Based on the introduction of the meaning and structure of social tagging, this paper mainly discusses the advancements of personalized information recommendation based on social tagging.
本文在对社会化标注的内涵和结构加以简单介绍的基础上，重点探讨了基于社会化标注进行推荐的相关进展。
Collaborative Filtering is frequently used in solving information overload problem, Collaborative Filtering is a main tool used in Personalized Recommendation.
协同过滤是经常被采用的解决信息过载问题的方法，是个性化推荐的主要方法之一。
The personalized services realize the purpose of initiative recommendation by collecting and analyzing the information of customers and study the interests and behavior of them.
个性化服务通过收集和分析用户信息来学习用户的兴趣和行为，从而实现主动推荐的目的，为不同用户提供不同的服务，以满足不同的需求。
A new challenge to personalized recommendation is provided when problem of system information overload appears.
信息过载问题的出现，为个性化推荐系统提供了新的挑战。
Personalized recommendation system (hereinafter referred to as PRS) applied to the fields of e-commerce and information services early, and has been relative mature.
个性化推荐系统(简称prs)最早应用于电子商务和信息服务领域，现已相对成熟。
ALIRS also supplies the personalized services such as key information extraction and valuable information recommendation.
提供关键信息抽取、有价值信息自动推荐等个性化服务。
Compared with the traditional personalized recommendation model, this one had higher speed and better accuracy, which provided important guiding value for many personalized information servers.
该模型较传统的个性化推荐在的速度和准确性上都有较大的改善，应用领域广泛，为个性化信息服务的提供者提供了很好的参考价值。
Compared with the traditional personalized recommendation model, this one had higher speed and better accuracy, which provided important guiding value for many personalized information servers.
该模型较传统的个性化推荐在的速度和准确性上都有较大的改善，应用领域广泛，为个性化信息服务的提供者提供了很好的参考价值。
应用推荐