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2015 IEEE 12th International Conference on e-Business Engineering最新文献

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Privacy Preserving-Based Recommendation Service Model of Mobile Commerce and Anonimity Algorithm 基于隐私保护的移动商务推荐服务模型及匿名算法
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.77
Chunhui Piao, Xiaoyan Li
The wide location based service in the application of mobile commerce has brought great convenience to people's work and lives, while the risk of privacy disclosure has been receiving more and more attention from the academia and industry. After analyzing the privacy issues in mobile commerce, a privacy preserving recommendation service framework based on cloud is established. According to the defined personalized privacy requirements of mobile users, the (K, L, P)-anonymity model is formally described. Based on the anonymity model, a dynamically structure minimum anonymous sets algorithm DSMAS is proposed, which can be used to protect the location, identifier and other sensitive information of the mobile user on the road network. Finally, based on a real road network and generated privacy profiles of the mobile users, the feasibility of algorithm are validated by experimentally analyzing using the metrics including information entropy, query cost, anonymization time and dummy ratio.
移动商务应用中广泛的基于位置的服务给人们的工作和生活带来了极大的便利,同时隐私泄露的风险也越来越受到学术界和业界的关注。在分析了移动商务中的隐私问题后,建立了一个基于云的隐私保护推荐服务框架。根据定义的移动用户个性化隐私需求,对(K, L, P)-匿名模型进行形式化描述。在匿名模型的基础上,提出了一种动态结构最小匿名集算法DSMAS,该算法可用于保护道路网络中移动用户的位置、标识符等敏感信息。最后,基于真实道路网络和生成的移动用户隐私概况,利用信息熵、查询成本、匿名化时间和虚拟比例等指标进行实验分析,验证了算法的可行性。
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引用次数: 3
Personalized E-Advertisement and Experience: Recommending User Targeted Ads 个性化电子广告与体验:推荐针对用户的广告
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.19
D. A. Qudah, A. Cristea, Suncica Hadzidedic, Samar Al-Saqqa, Ali Rodan, Wei Yang
Personalized e-advertising is the art of attracting users' attention by correlating to their tastes and interests. The evolving research of adaptive hypermedia with its techniques and theories contributed to the personalization field. This paper reports the case study of "My Ads", an adaptive e-advertisement delivery system that is based on a new theoretical framework, to evaluate users' acceptance of personalized ads. The results indicated that the implemented features within the system contributed to an enhanced experience through the exposure to different personalization methods and the appealing ideas of the system.
个性化电子广告是通过与用户的品味和兴趣相关联来吸引用户注意力的艺术。自适应超媒体及其技术和理论的不断发展为个性化领域做出了贡献。本文以基于新理论框架的自适应电子广告投放系统“我的广告”为例,评估用户对个性化广告的接受程度。结果表明,系统内实现的功能通过接触不同的个性化方法和系统的吸引人的想法,有助于增强体验。
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引用次数: 6
Controlling Elasticity Dependencies for Multi-tenant Business Process 控制多租户业务流程的弹性依赖关系
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.50
Wael Sellami, Hatem Hadj Kacem, A. Kacem
One of the key properties driving the popularity of cloud computing is the elasticity of multi-tenant business process. However, performing elasticity at the business process and the SaaS (Software as a Service) levels independently may only result in significant resources waste relating to the scalability, complex logic and long-running of the cloud applications. In this paper, we propose a holistic approach to dynamically manage elasticity mechanisms based on functional dependencies between the multi-tenant process and its involved services. This research is based on a service pattern for enabling multi-level elasticity control and analyzing the elasticity impact of invoked services on quality of the affected processes. Furthermore, we define an auto-scaling algorithm for enforcing multi-criteria dependencies for the elasticity control. Evaluation of our approach on a realistic situation shows its efficiency.
推动云计算普及的关键属性之一是多租户业务流程的弹性。然而,在业务流程和SaaS(软件即服务)级别单独执行弹性可能只会导致与云应用程序的可伸缩性、复杂逻辑和长时间运行相关的大量资源浪费。在本文中,我们提出了一种基于多租户进程及其相关服务之间的功能依赖关系来动态管理弹性机制的整体方法。本研究基于一种服务模式,该模式支持多级弹性控制,并分析被调用服务对受影响流程质量的弹性影响。此外,我们定义了一种自动缩放算法,用于实施弹性控制的多标准依赖关系。对我们的做法在现实情况下的评价表明它是有效的。
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引用次数: 3
Joint Design Model of Multi-period Reverse Logistics Network with the Consideration of Carbon Emissions for E-Commerce Enterprises 考虑碳排放的电子商务企业多周期逆向物流网络联合设计模型
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.78
Xinxin Liu, Jianquan Guo, Chengji Liang
With the rapid development of E-commerce, the demand for forward and reverse logistics for E-commerce enterprises is becoming increasingly urgent. This paper proposes a joint design model of multi-period reverse logistics network with the consideration of carbon emissions for E-commerce enterprises. And a case study of E-commerce enterprises is used to verify the feasibility of the model. The result indicates that, this joint design model of multi-period reverse logistics network is more accordant with reality, the total operation cost of multi-period model reduces a lot and the carbon emission reduces greatly. Furthermore, this research provides additionally reference for reducing carbon missions as well as the designing of regional reverse logistics network for E-business enterprises, and even for other kinds of enterprises.
随着电子商务的快速发展,电子商务企业对正向和逆向物流的需求日益迫切。本文提出了考虑碳排放的电子商务企业多周期逆向物流网络联合设计模型。并以电子商务企业为例验证了该模型的可行性。结果表明,该多周期逆向物流网络联合设计模型更符合实际,多周期模型的总运行成本大大降低,碳排放量大大降低。此外,本研究还为电子商务企业乃至其他类型企业的碳减排和区域逆向物流网络的设计提供了额外的参考。
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引用次数: 6
Topic Based Information Diffusion Prediction Model with External Trends 具有外部趋势的基于主题的信息扩散预测模型
Pub Date : 2015-10-01 DOI: 10.1109/ICEBE.2015.15
Di Wu, Chunping Li, Raymond Y. K. Lau
Information diffusion model plays an important role in many real-world applications such as online marketing and e-government campaigns. Existing approaches often predict information diffusion by examining whether events are triggered by external trends or the social network itself. However, existing methods cannot take into account the semantically rich "topics" to estimate the correlations between users and messages describing some events. The main contribution of our work is the development of the Topic based Information Diffusion (TBID) model which can incorporate external trends model and topic based social descriptions to enhance the effectiveness of predicting information diffusion in online social networks. Experiments conducted based on real-world data sets confirm the distinct advantage of the proposed computational method. Our research opens the door to the development of a more effective personalized information recommendation model in online social media.
信息扩散模型在网络营销和电子政务运动等现实应用中发挥着重要作用。现有的方法通常通过检查事件是由外部趋势还是社会网络本身引发来预测信息扩散。然而,现有的方法不能考虑语义丰富的“主题”来估计用户与描述某些事件的消息之间的相关性。本文的主要贡献是建立了基于主题的信息扩散模型(TBID),该模型将外部趋势模型与基于主题的社会描述相结合,提高了在线社交网络中信息扩散预测的有效性。基于真实数据集的实验证实了所提出的计算方法的明显优势。我们的研究为在线社交媒体中更有效的个性化信息推荐模型的发展打开了大门。
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引用次数: 2
期刊
2015 IEEE 12th International Conference on e-Business Engineering
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