上下文感知的高铁信息服务推荐方法研究

针对如何为高铁站旅客即时提供高效的个性化服务问题,将上下文信息引入到服务推荐过程中,对用户上下文信息按照时间、空间、用户、应用四个方面进行数据分析处理,采用改进FP-Growth算法,使之支持对二维数据项的挖掘,获取上下文与服务功能之间的关联规则。通过与当前上下文信息的相似度计算,构造出当前应用场景下可用的个性化服务集合。实验证明该方法可提高服务匹配的准确率和命中率,有助于提升旅客服务满意度。     

移动社会网络中基于多维上下文匹配的数据转发算法

通过研究移动社会网络中的多种上下文信息对节点移动模式的影响,提出了基于多维上下文认知的数据转发算法MCMF。该算法综合考虑物理邻接性、社会相似性以及社会交互性3个维度的上下文信息来进行动态数据转发决策。首先消息携带者节点通过物理邻接匹配获得邻居节点集合;然后通过社会相似性匹配在邻居节点集合中选出候选节点子集,并基于社会网络的社群特征,采用马尔可夫预测方法在候选节点子集中选出最优中继节点;最后设计高效的数据转发算法。仿真实验表明,相比于其他3种著名算法,该算法在交付比率和开销比率方面具有较好的性能。     

普适计算服务匹配技术研究

在普适计算环境下需要根据用户的需求提供合适的服务,这需要对用户请求的服务和环境提供的服务进行服务的匹配.而目前使用的基于语法的服务匹配和基于语义的服务匹配都不能很好地适应普适计算环境的高效、资源约束和上下文感知的要求.通过分析普适计算环境下主要的基于语法的和基于语义的服务匹配技术,给出普适计算环境下在高效、资源约束和上下文感知的特殊要求下服务匹配的解决方案,并就面向服务组合的服务匹配进行了分析.     

上下文感知的移动社交网络服务选择机制研究

服务选择机制作为为用户提供智能性、主动性应用服务的一项关键支撑技术,是移动社交网络中重要的研究内容之一.文中提出了基于上下文、信任网络和协作过滤算法的移动社交网络服务选择机制,将上下文相似度引入到服务选择的过程中,并且和信任度相结合,构成"用户-服务-上下文"三维协作过滤服务选择模型.该方法提高了服务选择的准确性和可靠性,避免了服务选择的盲目性和随意性.仿真实验表明,与传统的协作过滤推荐算法相比,该服务选择算法具有更高的准确率.     

基于用户聚类和移动上下文的矩阵分解推荐算法研究

随着移动互联网技术的快速发展,越来越多的用户通过移动设备获取移动信息和服务,导致信息过载问题日益凸出。针对目前上下文感知推荐算法中存在的数据稀疏性差、上下文信息融入不够、用户相似性度量被忽略等问题,提出一种基于用户聚类和移动上下文的矩阵分解推荐算法。该算法通过利用k-means对用户聚类找到偏好相似的用户簇,求出每簇中并对 用户所处上下文之间的相似度并对其进行排序,由此找出与目标用户偏好和上下文均相似的用户集合,借助该集合改进传统矩阵分解模型损失函数,并以此为基准进行评分预测和推荐。仿真实验结果表明,所提算法可有效提高预测评分的准确度。     

一种基于上下文协商的动态服务组合方法

普适计算的计算环境和交互信息动态变化,为了提供适时适地的服务,服务组合除了满足用户的需求之外,还要适应环境的变化.以面向普适计算的分布式文档管理系统为例,提出一种基于上下文协商的动态服务组合方法,适应普适计算环境下资源动态变化的特点,同时满足用户对服务的需求.首先定义上下文和带有上下文信息的服务模型;然后给出服务和设备以及服务和用户之间的上下文协商约束条件,根据约束条件提出基本算法实现服务动态组合,并对基本算法进行优化;最后通过原型系统和实验验证算法的性能和有效性,并通过实验数据分析上下文对于服务组合的影响.实验数据说明:提出的方法能够应用在普适计算环境中上下文敏感的服务组合问题上,提高服务组合的动态适应性和网络资源利用率.     

一种基于DFA的服务行为模型及其应用

本文对Web服务行为描述进行深入分析,在构造web服务自动集成结构基础上,对原有限自动机定义进行语义扩展和候选集扩展,达到准确地描述Web服务间的执行步骤、行为间简单逻辑运算关系和代价选择运算关系目的.完成服务提供商提供服务流与用户期望在该结构下的自动匹配,为web服务自动集成提供了理论依据.     

本体匹配的网格服务发现模型研究

如何从大规模网格服务集合中快速而准确地发现满足用户请求的服务,是语义环境下网络应用的一个重要方面。针对传统的基于关键字匹配的Web服务发现方法无法准确描述网格服务服务能力和应用领域的问题,提出了一种基于输入和输出领域本体的语义网格服务描述模型和基于本体匹配的语义网格服务发现流程,构造了基于本体匹配语义相似度计算的语义网格服务发现算法。实验结果表明,基于本体匹配的语义网格发现方法能够获得很好的查全率和查准率。     

大数据环境下基于K中心点优化算法的Web服务组合

在当前Web服务海量增加、现有Web服务选择算法低效、用户匹配度差的基础上，针对K中心点算法存在的质点偏移、准确率低和容易发生畸变等问题，提出一种大数据环境下基于K中心点优化算法的Web服务组合方法。该方法是在大数据环境下，根据不同用户需求满意度及Web服务QoS参数，对基于优化初始聚类中心的K中心点算法的Web服务选择及最优Web服务组合进行研究。同时针对不同的选择方法对服务动态选择及组合的准确度、迭代更新次数、候选集选择时间及选择总时间进行实验分析，验证了本文研究方法的有效性和可靠性。     

基于移动代理的上下文感知系统研究

上下文表是用上下文信息描述实体状态,原子上下文感知反应则说明了系统根据当前上下文和历史上下文做出合适的响应.基于以上两个概念设计了上下文感知移动代理、系统代理和上下文感知移动代理服务环境,目的是解决普适计算系统需要自动适应用户行为及环境变化的问题.首先使用历史上下文与当前上下文提取上下文表达式,根据该表达式在上下文反应容器中匹配对应的操作,然后由系统代理执行该操作,为用户提供任务相关的服务或者信息.其次根据原子上下文感知提出若干实例,并由上下文感知演算验证,同时指出上下文感知演算的不足.最后,用染色Petri网对一个实例场景仿真,证明了系统的可行性.     

Ubiquitous enterprise service adaptations based on contextual user behavior

Recent advances in mobile technologies and infrastructures have created the demand for ubiquitous access to enterprise services from mobile handheld devices. Further, with the invention of new interaction devices, the context in which the services are being used becomes an integral part of the activity carried out with the system. Traditional human–computer interface (HCI) theories are now inadequate for developing these context-aware applications, as we believe that the notion of context should be extended to different categories: computing contexts, user contexts, and physical contexts for ubiquitous computing. This demands a new paradigm for system requirements elicitation and design in order to make good use of such extended context information captured from mobile user behavior. Instead of redesigning or adapting existing enterprise services in an ad hoc manner, we introduce a methodology for the elicitation of context-aware adaptation requirements and the matching of context-awareness features to the target context by capability matching. For the implementation of such adaptations, we propose the use of three tiers of views: user interface views, data views, and process views. This approach centers on a novel notion of process views to ubiquitous service adaptation, where mobile users may execute a more concise version or modified procedure of the original process according to their behavior under different contexts. The process view also serves as the key mechanism for integrating user interface views and data views. Based on this model, we analyze the design and implementation issues of some common ubiquitous access situations and show how to adapt them systematically into a context-aware application by considering the requirements of a ubiquitous enterprise information system.

An adaptive algorithm for QoS-aware service composition in grid environments

Service composition enables users to realize their complex needs as a single request and it has been recognized as a flexible way for resource sharing and application integration since the appearance of Service-Oriented Architecture (SOA). For each of the needed individual services there may be many candidate services available presented by different vendors and with different functional and non-functional properties such as Quality of Service (QoS). Approaches are needed to select candidate services with various QoS levels according to user’s performance requirements meanwhile adapt to dynamic churn in grid environments. This paper mainly focuses on adaptive management of QoS-aware service composition in grid environments and proposes an adaptive algorithm for QoS-aware service composition (AQSC). In AQSC we model this problem as the Multi-Constrained Optimal Path selection problem (MCOP) and use heuristic approach for service selection, then backup services set is introduced as an adaptive mechanism so as to ensure the fulfillment of composite service when some candidate services fail or withdraw. Both theoretical analysis and simulation results indicate that AQSC has high composition success rate, finish rate and low cost.     

智慧城市中QOE感知服务组合策略的研究

无线传感器的发展和物联网技术的应用,配有物联网的设备正以一种全新的“智能终端服务”的形式进入人类生活,要想在复杂冗余的物联网环境中寻得满足不同用户需求的服务,需要考虑服务组合的概念。为此,在对传统服务组合研究方法深入分析的基础上,提出了智慧城市的服务组合选择策略。首先根据物联网应用服务的多样性,通过改进蚁群算法获得用户对服务的偏好顺序,然后使用层次化QOE评价模型量化客户体验质量,进而选出最优服务组合提供给用户。根据提出的服务组合策略,给出服务选择具体的实施流程,通过仿真模拟表明基于改进蚁群算法的服务组合策略在服务选择问题上具有一定的推广价值。     

Deploying personalized mobile services in an agent-based environment

The mobile Internet allows users to obtain digitized contents and services from wired and wireless networks virtually anywhere at any time via different handheld mobile devices. However, due to the distinct features of mobile users, mobile devices and wireless networks, deploying mobile services is not as straightforward as generally expected. To ensure the success of mobile services, this paper presents a multi-agent framework that considers different contexts to support personalized services on wireless networks. In the proposed approach, client users, content providers, and service providers are all considered as software agents. They interoperate on the same platform to request and deliver mobile services. The most important issues related to agent operations and context awareness in an agent world are also discussed and analyzed. To verify our framework, different application services are developed accordingly on a publicly available middleware platform. Experiments are conducted for both services to evaluate their corresponding performance. The preliminary results show that our multi-agent approach to personalization is promising and efficient in the deployment of mobile services.     

基于改进蚁群算法的服务组合研究

在服务计算过程中,服务组合问题是其中关键的技术之一。在原子候选服务数目巨大的情况下,经典的算法一般都是寻找问题的最优解,存在运算量大,运行时间长的缺点,蚁群算法并不是寻找服务组合问题的最优解,而是得到用户能够认同的可行解。为了能够更有效的为用户提供各种服务,在静态的服务组合建立过程中,以服务发现的候选原子服务集合中的服...     

Mobile payment services adoption across time: An empirical study of the effects of behavioral beliefs, social influences, and personal traits

Mobile payment is an emerging and important application of mobile commerce. The adoption and use of mobile payment services are critical for both service providers and investors to profit from such an innovation. The present study attempts to identify the determinants of pre-adoption of mobile payment services and explore the temporal evolution of these determinants across the pre-adoption and post-adoption stages from a holistic perspective including behavioral beliefs, social influences, and personal traits. A research model that reflects the characteristics and usage contexts of mobile payment services is developed and empirically tested by using structural equation modeling on datasets consisting of 483 potential adopters and 156 current users of a mobile payment service in China. Our findings show that behavioral beliefs in combination with social influences and personal traits are all important determinants for mobile payment services adoption and use, but their impacts on behavioral intention do vary across in different stages. Theoretical and practical implications of the findings are presented.     

Effect of use contexts on the continuous use of mobile services: the case of mobile games

As mobile services become more popular and people can use them virtually anywhere, research on the effect of use contexts is gaining more attention. This research presents results from a study of continuous use of mobile services in different use contexts as defined by task and consumption place. Using mobile games as an example, the authors proposed a research model that augments current technology adoption theories to fit the hedonic nature of mobile games. The results from conducting an online survey indicate that contextual factors have significant moderating effect on the intention to play mobile games. The diverse lifestyles of users also have different attitudes and concerns regarding using mobile services. The findings suggest that service providers need to take into account the impact of use contexts and the needs of specific users when they design mobile services.     

自定义服务质量模型的网格工作流调度算法

随着网格服务应用的发展,在网格工作流中,复杂的任务可以由多个独立的服务,通过工作流引擎等方式组合成新服务后完成。在组合服务的过程中,由不同服务提供商提供的候选服务,具有不同的服务质量参数,在网格工作流调度中,需要满足用户定义的服务质量约束。提出了方便用户定义的服务质量模型,并且在该模型的基础上,改进了网格工作流调度算法,通过实验分析证明改进后的算法优于传统的调度算法。     

A decision-making method for personalized composite service

Web services are emerging technologies that enable application to application communication and reuse of autonomous services. Web services composition is a concept of integrating component services to conduct complex business transactions based on functionality and performance constraints. With the rapid growth of Web services on the Internet, the services owing the same functionality and different performance become more and more, and different users care for different quality. Therefore, designing effective decision-making method for the personalized composite service has become a fundamental problem for the application based on Web service. In this paper, oriented to the user need with single optimization objective, an efficient algorithm, which consists of Particle Swarm Optimization (PSO) and Niche technology, is presented to solve the Web service selection problem. Furthermore, in view of the practical composition requirements including multiple optimization objectives, an algorithm used to resolve the service selection with multi-objective multi-constraint is designed based on NPSO and the intelligent optimization theory of multi-objective PSO, which can produce a set of Pareto optimal composite services by means of optimizing various objective functions simultaneously. Experimental results show that NPSO algorithm owns better global convergence ability with faster convergence speed. Meanwhile, multi-objective multi-constraint NPSO is both feasible and efficient.