本文主要研究协同电子商务环境下的经销商管理系统的设计与实现。
The primary purpose of this thesis is to study design and realization of dealer management system in the Collaborative E-Business Environment.
文章采用面向服务体系（SOA）的思想，用网格服务构建了一个协同电子商务平台。
We used the idea of the Service Oriented Architecture (SOA) and Grid Service to build a collaborative e-business platform.
分析了协同电子商务的定义和思想，讨论了协同电子商务平台的需求、体系结构、功能分析、特点和服务模式。
Then it was discussed that the requirements, architecture, functions, characteristics and service-mode of the collaborative e-business platform.
该文提出了协同电子商务的一种应用模式，对应用模式进行了全面的分析、设计，并对系统开发的关键实现技术进行了讨论。
This paper brings forward one kind of the cooperating electronic business application modes, fully analyzes, designs the mode and also discusses the pivotal technology in the system developing.
针对该问题，给出了一种基于SAML的安全数据交换服务和基于该服务的面向企业应用协作的协同电子商务安全服务系统。
In this paper, the authors present a new SAML-based security information exchange service and a cooperative e-Commerce security service system for enterprise application integration.
电子商务系统规模的日益扩大，协同过滤推荐方法也面临诸多挑战：推荐质量、可扩展性、数据稀疏性、冷开始问题等等。
But, with expansion of E-commerce system's size, collaborative filtering approach suffer from many challenges, for instance, quality of recommendations, scalability, sparsity, cold-start problem.
协同商务、流程管理和工作流技术是电子商务、管理思想和计算机应用领域研究的热点。
Collaborative Commerce, flow management and Workflow technology are the hotspots of E-business, management idea and computer application research.
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。
In E-commerce recommender system, collaborative filtering technology is the most popular and successful method at present.
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 is thriving among lots of personalized recommendation technology which leads the recommendation system trends of major e-commerce platforms.
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。
Collaborative filtering recommendation algorithm is one of the most successful technologies in thee-commerce recommendation system.
受电子商务研究领域中相关研究成果启发，我们尝试将协同过滤推荐技术引入学习资源的个性化推荐研究中。
Be inspired by the research achievement in e-commerce fields, we try to introduce the collaborative filtering technology into research of personalized recommendation of learning resources.
将这些理论应用于电子商务项目协同管理系统中，促进了企业的管理基础和能力水平的提高。
By using these theories in the ECPCM, the dissertation promotes the management foundation and ability level higher.
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。
Absrtact: In E- commerce recommender system, collaborative filtering technology is the most popular and successful method at present.
应用推荐