Personalization recommendation is a valid method for lightening the user's burden on information retrieval.
个性化推荐是一个有效的减轻用户的负担，对信息检索的方法。
Firstly the deficiency of the personalization recommendation based on cluster mining technology was analyzed in detail.
首先，详细分析了目前基于聚类挖掘技术的个性化推荐方法的若干不足之处。
The paper presents a personalization recommendation system based on search result by combining content-based filtering technol.
本文研究的是在线渠道这一新的信息媒介中，消费者信息搜索效果的影响因素。
This paper presents a multidimensional association rules recommendation system which provides more exact personalization recommendation for customer.
提出了一种多维关联规则推荐系统，为客户提供更加准确的个性化推荐。
In order to alleviate the pressure of information overloading and enhance consumer satisfaction, personalization recommendation service came into being.
为了缓解信息过载的压力，提升消费者的满意度，个性化推荐服务应运而生。
Personalization recommendation technique is an important technology in E_commerce, but how to provide recommendation service in net site which is not E_commerce is becoming a hot research now.
个性化推荐技术是电子商务系统中重要的技术，但对一般的非商务型网站如何向用户提供推荐服务成为当前研究的热点。
The search engine, combined with the personalization and the recommendation engines, are the primary components in the infrastructure of an efficient IP-TV portal.
搜索引擎以及个性化和建议引擎是高效的IP - tv门户的基础设施中的主要组件。
"If web 2.0 could be summarized as interaction, web 3.0 must be about recommendation and personalization," she wrote.
“如果web 2.0可被概括为交互，web 3.0就一定会是有关推荐和个性化”，她这样写道。
If, as a developer, you know these things, you can improve the user experience and content through AD targeting, personalization, and recommendation.
如果你是一名开发者，知道这些以后，你就可以通过广告定位、人性化以及推荐机制改善用户体验和内容。
The State of Recommendation Engines is a sponsored content series by BT Buckets, a leader in personalization and onsite behavioral targeting.
目前，该推荐引擎也是BTBuckets (Google的用户切分及服务优化工具)的一项赞助内容。
His research interests include recommendation systems, personalization, data mining, and artificial intelligence.
他的研究兴趣包括推荐系统、个性化、数据挖掘以及人工智能。
Forth, complete the implementation of the algorithm, integrate it into the existing CADAL Digital Library Portal personalization module and achieve better recommendation effectiveness.
完成了该算法的实现，并集成到现有的CADAL数字图书馆门户个性化模块中，达到了较理想的推荐效果。
Some Suggestions are presented on customer profile data mining, recommendation systems data mining, Web personalization data mining, multimedia data mining, and buyer behavior data mining.
并且针对电子商务在顾客资料、顾客建议、个性化要求、多媒体应用、购买者的行为等方面的数据采集问题，提出了有效的应用性。
Some Suggestions are presented on customer profile data mining, recommendation systems data mining, Web personalization data mining, multimedia data mining, and buyer behavior data mining.
并且针对电子商务在顾客资料、顾客建议、个性化要求、多媒体应用、购买者的行为等方面的数据采集问题，提出了有效的应用性。
应用推荐