Therefore, How to build an effective collaborative commerce system, which can resolve these three problems, needs to be researched currently.
如何构建一个能有效解决这些问题实现跨网络系统集成的多点交互协同商务系统是当前需要研究的前瞻性问题之一。
Collaborative commerce oriented CC-GDSS model that based on group decision support system holds out the construction of collaborative commerce system commendably.
基于群体决策支持系统的面向协同商务的CC - GDSS模型的提出很好地支持了协同商务系统的构建。
Facing the question of the choice to the software, it offers collaborative commerce system software choosing overall principle and concrete principle, and carries on concrete analysis to it.
针对软件选择问题，提供了协同商务系统软件选型总体原则和具体原则，并对其进行了具体的分析。
In Chapter 5, the realization of secure data exchange system of Collaborative Commerce Platform, the secure result analysis and exception analysis are described.
第5章介绍协同商务平台安全数据交换系统的实现，安全结果分析和异常分析。
In Chapter 4, the design of the data exchange system of Collaborative Commerce Platform based on the security model is discussed.
第4章主要介绍了基于该安全模型的协同商务平台数据交换系统的设计。
NET technology, design and develop the negotiation system based on collaborative commerce platform, to support the core enterprise and its partners 'online interact.
NET技术，设计开发了基于协同商务平台的协商系统，以支持核心企业与合作伙伴进行网上交互。
In E-commerce recommender system, collaborative filtering technology is the most popular and successful method at present.
电子商务推荐系统中协同过滤已成为目前应用最广泛、最成功的推荐方法。
Collaborative filtering is thriving among lots of personalized recommendation technology which leads the recommendation system trends of major e-commerce platforms.
众多个性化推荐技术中协同过滤可谓一枝独秀，该算法引领了当今各大电子商务平台的推荐系统的发展趋势。
Collaborative filtering recommendation algorithm is one of the most successful technologies in thee-commerce recommendation system.
协同过滤推荐算法是在电子商务推荐系统中最成功的技术之一。
Absrtact: In E- commerce recommender system, collaborative filtering technology is the most popular and successful method at present.
摘 要：电子商务推荐系统中协同过滤已成为目前应用最广泛、最成功的推荐方法。
Absrtact: In E- commerce recommender system, collaborative filtering technology is the most popular and successful method at present.
摘 要：电子商务推荐系统中协同过滤已成为目前应用最广泛、最成功的推荐方法。
应用推荐