推荐系统
- 网络recommender system;Recommendation System;recommender
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Web推荐系统能为用户提供有针对性的个性化服务。
Web recommender system can provide different users with different services .
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应用语义网构建Web服务推荐系统
Buiding a Web Service Recommender System Based on the Semantic Web
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基于Web日志和缓存数据挖掘的个性化推荐系统
Personalization Recommendation System Based on Web Log & Cache Data Mining
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基于Web日志和商品分类的协同过滤推荐系统
Collaborative Filtering Recommendation System Based on Web Log and Commodities Classification
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在传统Web推荐系统的基础上引入了反馈机制。
This paper adds a feedback mechanism into Web recommendation system ;
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基于Web日志挖掘的自适应网站推荐系统框架研究
The Research on Self-adaptive Websites Recommendation System Framework Based-on Web Log Mining
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设计并实现基于Web日志挖掘的个性化推荐系统原型。
Design and implement a web log based personalized prototype recommendation system .
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基于Web日志的因特网协作推荐系统的研究
Research on the Web Log Based Internet Collaborative Recommendation System
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复杂分布式Web系统推荐系统问题。
Web recommendation system of complex distributed systems problems .
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基于模糊兴趣集和智能Agent的推荐系统模型研究
Model of recommender system based on fuzzy interest set and intelligence agent
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在基于人工免疫增量的聚类算法基础上,设计了基于Web挖掘的电子商务推荐系统模型。
Based on artificial immune incremental clustering algorithm , designed the Web-based E-Commerce recommendation system model .
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基于Agent的个性化推荐系统的研究
Research on Agent-Based Personalized Recommendation System
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在基于Web使用挖掘的推荐系统中,仅采用关联规则挖掘技术的Web推荐系统在预测用户未来浏览模式时很难取得令人满意的结果。
In the personalized recommendation systems , the resulting association patterns do not perform well in predicting future browsing patterns .
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本文使用多准则排序作为替代,描述了一种基于多Agent技术的推荐系统。
Using multi-criteria ratings instead , this paper describes a novel recommender system relying on the multi-agent technique .
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随着Web信息量的快速增长,个性化的Web信息推荐系统扮演着越来越重要的角色。
As fast growing of Web information , personal Web recommendation system would play more and more im - portant role .
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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。
Web personalized recommender systems anticipate the needs of web users and provide them with recommendations according to their navigation patterns .
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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。
So , the implementation of web PRSs based on voting mechanism and technologies , is becoming a hot topic for researchers .
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探讨了电子商务、电子商务推荐系统与个性化服务、电子商务中进行Web挖掘的数据源、获取的知识模式以及Web挖掘在电子商务活动中的应用;
Especially we analyze E-Commerce , including its personalized recommendation system , its data sources , its related technologies and its application fields .
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基于社区驱动与Web数据挖掘的个性化e-learning解决方案推荐系统研究
Research of Personalized E-learning Solution Recommending System Based on Community Driving and Web Data Mining
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集成AHP和数据挖掘的个性推荐系统研究
Research on Recommendation System Combining AHP and Data Mining
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基于组件式GIS技术开发了精准农业变量施肥处方推荐系统。
Based on the technology of ComGIS , the recommend system for variable-rate fertilization in precision agriculture was developed .
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基于Multi-agent的个人电脑客户定制服务推荐系统
Intelligent Recommendations System of Made-to-order PC Based on Multi-agent
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文本聚类是Web文本挖掘中的一个非常重要的技术,它已经被广泛地应用于信息管理、搜索引擎、推荐系统等多个领域。
Text clustering , which is known as the significant technique of Web text mining , has been applied in Information Management , Search Engine .
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基于网络的智能系统研究是WEB挖掘和网上智能的重要研究方向,而智能推荐系统(IntelligentRecommendationSystem)又是网上智能系统的典型应用。
Web-based intelligent system is an important aspect of DM and WI . Intelligent Recommendation System is a kind of typical web-based intelligent application system .
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个性化Web推荐系统是利用用户的浏览行为定制符合用户结构和内容的过程。
The personal Web recommendation system is the process to use the user 's browsing behaviors to work out the structures and contents in coincidence with the users .
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个性化推荐系统(RecommenderSystem)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。
The personalized recommender system as a important information filtration mean is a potential method to solve the problem of information overload currently .
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基于E-Learning的社区监控及个性化推荐系统的实现
Realization and Research on Community Monitoring & Personalized Recommendation System Based on E-Learning
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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。
This framework mainly contained the functions of human-computer interaction , user interest learning , system data management , information search , agent collaboration and so on .
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利用Web日志文件采用网页被用户选择的频率作为权重值,实现了个性化推荐系统的算法。
By using Web log file , making use of the Web page frequency which is visited by users as its weight , the algorithm is implemented in the personalization recommendation .
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对于那些想找找有什么书可以看的人,Oyster的推荐系统还是不错的。
For those looking to discover a Book spontaneously , oyster will do just fine .