构建个性化智能移动电子商务系统的关键技术与方法研究
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摘要
信息经济席卷全球,成为经济运行的主流,电子商务作为一种重要的商业运营模式已渗透到国民经济、社会服务、人类生活的各个领域,给人们的生活带来了巨大的影响。同时,随着移动通信技术以及移动终端设备等技术的发展,人类正在进入以移动互联网为中心的移动信息时代。移动电子商务正是凭借其服务对象的移动性、服务要求的即时性、服务终端的私人性和服务方式的方便性等新颖的特性,显示出强大的生命力,具有很大的潜在应用前景。
然而目前移动终端设备屏幕狭小、文本输入方式单一、输入不便、电池寿命短、存储与计算处理能力有限等问题以及所处无线网络环境的带宽有限或不稳等限制,使得移动客户端和服务器之间还很难保持长期稳定的连接,对移动用户开展一些关键商务活动带来诸多不便；对于目前大量移动电子商务应用,用户需要频繁地访问服务去获取交易的机会,这需要消耗大量的时间和精力去从海量的商品或服务去寻找自己所需的信息；另外,移动电子商务与现有的电子商务一样仍然处于初级阶段,繁琐复杂的商务活动(商品、服务查询或浏览,选择、协商、选购、支付、运输、售后服务等)仍缺乏一种自动化的流程,仍需要用户积极参与每个步骤的商务活动。因此,目前在移动环境下缺乏一个高效开展繁琐商务活动的平台。
本文结合移动代理、Web服务、上下文感知计算以及工作流等新颖技术,构建了一个CUB (Call U Back)个性化的智能移动电子商务平台。
首先,充分利用了Web服务和多代理系统的优势,并参考了WSDL与OWL-S对服务的描述方法,我们提出了一个统一的CUB服务描述框架,使其能充分地表达服务的功能和行为的能力。我们也提出了一个CUB服务质量模型,对服务的非功能属性信息进行统一的描述。最主要的是在本文中提出了抽象服务概念,其对一系列功能相同或相近功能的服务类型的高层抽象描述,用来屏蔽分布式网络平台所提供的服务(A-service与E-service)异构性与多样性问题；我们通过对抽象服务的编排进而组合成了一个抽象商务流程逻辑模型ABPL,为繁琐的多步骤商务活动提供了便利,实现更加强大更加完整的商业增值服务。
其次,根据移动电子商务中用户上下文以及服务信息领域知识信息的种类繁多、数据表达方式各异,采用本体建模的方法,建立了一套支持逻辑推理、便于知识共享,具有明确语义信息和指向性的上下文模型,包括移动电子商务个性化用户本体CUB_USER_ONT和移动电子商务领域服务本体CUB_SERVICE_ONT.
再次,提出了一个基于上下文能适应移动用户环境的动态变化和个性化需求的服务发现与选择框架。首先,我们主要设计了一个扩展UDDI标准规范的CUB服务发布中心CUB_UDDI,其能集成与发布Agent与Web服务两类服务,并增加了语义解析与语义扩展能力；其次,针对分布式网络的不稳定性以及服务具有不同的服务质量等因素,提出了基于用户上下文信息的服务发现与选择CUB_SDSA方法和基于上下文的复合工作流的服务发现与选择CUB_CWSDSM方法。其中CUB_SDSA方法首先根据请求用户与服务发布信息中的上下文的相似性,选择与用户当时情境相近的并能完成用户商务活动的功能服务,然后根据这些候选功能服务的QoS属性选择最优的；CUB_CWSDSM方法首先在局部流程服务发现阶段根据请求用户与服务发布信息中的上下文信息的相似性,为每个步骤的抽象服务选择与用户相关的能完成任务的功能候选服务,在全局服务选择过程根据局部最优原理,从而产生了全局最佳的工作流执行计划。最后,根据A-Service与E-Service的不同调用方式,提出了CUB服务调用模型,根据发现的服务具体描述激活具体的目标服务。
最后,我们构建了一个通过移动代理和Web服务交互模式的多层系统框架,使得消费者和商家可以从繁琐的交易环节中解脱出来,降低网上商务活动的网络通信代价。更重要的是通过建立一个移动商务原型系统,验证以及优化上述提出的方法与模型,从而探索出一套行之有效的开展智能商务活动模式,为更加广泛的推广移动电子商务应用打好基础。
With the rapid growth of Internet and its related technology over the last two decades, it makes significant change about every important realm of our modern life. One important variation of our daily lives is the way of conducting business. Clearly, Electronic commerce (E-commerce) is the most typical sample of internet applications. Meanwhile, At advent of the wireless network, mobile computing and their related technologies, mobile internet gradually becomes the important variation in landscape of mobile Information ages. M-commerce is an attractive research area due to its relative novelty, mobility, personality, and flexibility, and great potential in business applications.
In comparison to desktop-based computing paradigm, M-commerce has some limitations due to physical constraints of mobile handheld devices, such as small screen size, poor network connectivity, low limited battery capacity, limited storage and computing capacity. On one hand, it is expensive and unreliable when an amount of data has to be transferred between the client and the remote server. On the other hand, it is impossible to retain a long-time connectivity to maintain face-to-face communication between mobile consumers and venders. In addition, the nomadic users need to frequently check trading opportunity, as well as carry out fuzzy and complex information exchange and decision-making tasks. Therefore, it leads to the raise of revenue and creates the risk of missing trade opportunities if the trade time is constrained by the limited availability of physical access to the service. It is well-known that an M-commerce transaction involves a sequence of activities, such as negotiation, purchasing, shipment, payment and logistic services. Existing M-commerce applications are lack of fully automated business processes and still require significant manual effort.
In this paper we present a general solution of integrating Web Service, Mobile Agent, Context-aware Computing and workflow technology to implement automated trading task and compose services dynamically in real time to create a highly personalized assistant.
Firstly, In order to get benefits of both Web Services and agent paradigm, we present a common Service Description Framework, which clearly presents the function and computing capability of concrete service. Furthermore, we define a comprehensive QoS Model to present the no-functional attributes of service. We bring forward the concept of Abstract Service (AS) and Abstract Business Process Logic (ABPL). Abstract Service is a high-level description of the capabilities and categorization of an atomic service with similar functionality. APBL which indicates the order of a collection of activities without the details of execution is to implement the additional function.
Secondly, We focus on an ontology-based Context Model, called CUB-ONT, which derives from a set of descriptive contextual information for sharing common knowledge and logical inference, it includes CUB_SERVICE_ONT and CUB_USER_ONT.
Thirdly, we propose an comprehensive approach for supporting automatic context-aware service discover and selection in a dynamic environment. In order to publish different kind of services and look up services automatically, we extended UDDI to add semantic-based service categorization and service request enhancement as separate layers on top of the UDDI. It is compliant with the universally adopted standard for service discovery. Service communities that are used to organize the large and heterogeneous service space, it also is a distributed and dynamic environment. Therefore, We propose then using multiobjective optimisation techniques to find a set of optimal solutions from which a user can choose the most interesting tradeoff in single service selection or compostion scenarios, namely, CUBSDSA and CUB_CWSDSM. They are both based on Context of mobile user and Qos Attributes of Service. For different type service, we propose a common Service Invocation Model.
In order to verify the feasibility of our proposal, we have developed a preliminary prototype of system components and function that are considered to be critical to the viability of our proposal. At last we conducted serveral experiments in the prototype. Experimental evaluation results demonstrate that the CUB_SDSA algorithm provides a scalable solution to deal with the context-aware service selection problem in single service selection scenarios and CUB CWSDSM approach provides and a flexible solution in the context of composition scenarios. We will make a further step to develop highly automated and dynamically adaptive mobile commerce systems in the future.
然而目前移动终端设备屏幕狭小、文本输入方式单一、输入不便、电池寿命短、存储与计算处理能力有限等问题以及所处无线网络环境的带宽有限或不稳等限制,使得移动客户端和服务器之间还很难保持长期稳定的连接,对移动用户开展一些关键商务活动带来诸多不便；对于目前大量移动电子商务应用,用户需要频繁地访问服务去获取交易的机会,这需要消耗大量的时间和精力去从海量的商品或服务去寻找自己所需的信息；另外,移动电子商务与现有的电子商务一样仍然处于初级阶段,繁琐复杂的商务活动(商品、服务查询或浏览,选择、协商、选购、支付、运输、售后服务等)仍缺乏一种自动化的流程,仍需要用户积极参与每个步骤的商务活动。因此,目前在移动环境下缺乏一个高效开展繁琐商务活动的平台。
本文结合移动代理、Web服务、上下文感知计算以及工作流等新颖技术,构建了一个CUB (Call U Back)个性化的智能移动电子商务平台。
首先,充分利用了Web服务和多代理系统的优势,并参考了WSDL与OWL-S对服务的描述方法,我们提出了一个统一的CUB服务描述框架,使其能充分地表达服务的功能和行为的能力。我们也提出了一个CUB服务质量模型,对服务的非功能属性信息进行统一的描述。最主要的是在本文中提出了抽象服务概念,其对一系列功能相同或相近功能的服务类型的高层抽象描述,用来屏蔽分布式网络平台所提供的服务(A-service与E-service)异构性与多样性问题；我们通过对抽象服务的编排进而组合成了一个抽象商务流程逻辑模型ABPL,为繁琐的多步骤商务活动提供了便利,实现更加强大更加完整的商业增值服务。
其次,根据移动电子商务中用户上下文以及服务信息领域知识信息的种类繁多、数据表达方式各异,采用本体建模的方法,建立了一套支持逻辑推理、便于知识共享,具有明确语义信息和指向性的上下文模型,包括移动电子商务个性化用户本体CUB_USER_ONT和移动电子商务领域服务本体CUB_SERVICE_ONT.
再次,提出了一个基于上下文能适应移动用户环境的动态变化和个性化需求的服务发现与选择框架。首先,我们主要设计了一个扩展UDDI标准规范的CUB服务发布中心CUB_UDDI,其能集成与发布Agent与Web服务两类服务,并增加了语义解析与语义扩展能力；其次,针对分布式网络的不稳定性以及服务具有不同的服务质量等因素,提出了基于用户上下文信息的服务发现与选择CUB_SDSA方法和基于上下文的复合工作流的服务发现与选择CUB_CWSDSM方法。其中CUB_SDSA方法首先根据请求用户与服务发布信息中的上下文的相似性,选择与用户当时情境相近的并能完成用户商务活动的功能服务,然后根据这些候选功能服务的QoS属性选择最优的；CUB_CWSDSM方法首先在局部流程服务发现阶段根据请求用户与服务发布信息中的上下文信息的相似性,为每个步骤的抽象服务选择与用户相关的能完成任务的功能候选服务,在全局服务选择过程根据局部最优原理,从而产生了全局最佳的工作流执行计划。最后,根据A-Service与E-Service的不同调用方式,提出了CUB服务调用模型,根据发现的服务具体描述激活具体的目标服务。
最后,我们构建了一个通过移动代理和Web服务交互模式的多层系统框架,使得消费者和商家可以从繁琐的交易环节中解脱出来,降低网上商务活动的网络通信代价。更重要的是通过建立一个移动商务原型系统,验证以及优化上述提出的方法与模型,从而探索出一套行之有效的开展智能商务活动模式,为更加广泛的推广移动电子商务应用打好基础。
With the rapid growth of Internet and its related technology over the last two decades, it makes significant change about every important realm of our modern life. One important variation of our daily lives is the way of conducting business. Clearly, Electronic commerce (E-commerce) is the most typical sample of internet applications. Meanwhile, At advent of the wireless network, mobile computing and their related technologies, mobile internet gradually becomes the important variation in landscape of mobile Information ages. M-commerce is an attractive research area due to its relative novelty, mobility, personality, and flexibility, and great potential in business applications.
In comparison to desktop-based computing paradigm, M-commerce has some limitations due to physical constraints of mobile handheld devices, such as small screen size, poor network connectivity, low limited battery capacity, limited storage and computing capacity. On one hand, it is expensive and unreliable when an amount of data has to be transferred between the client and the remote server. On the other hand, it is impossible to retain a long-time connectivity to maintain face-to-face communication between mobile consumers and venders. In addition, the nomadic users need to frequently check trading opportunity, as well as carry out fuzzy and complex information exchange and decision-making tasks. Therefore, it leads to the raise of revenue and creates the risk of missing trade opportunities if the trade time is constrained by the limited availability of physical access to the service. It is well-known that an M-commerce transaction involves a sequence of activities, such as negotiation, purchasing, shipment, payment and logistic services. Existing M-commerce applications are lack of fully automated business processes and still require significant manual effort.
In this paper we present a general solution of integrating Web Service, Mobile Agent, Context-aware Computing and workflow technology to implement automated trading task and compose services dynamically in real time to create a highly personalized assistant.
Firstly, In order to get benefits of both Web Services and agent paradigm, we present a common Service Description Framework, which clearly presents the function and computing capability of concrete service. Furthermore, we define a comprehensive QoS Model to present the no-functional attributes of service. We bring forward the concept of Abstract Service (AS) and Abstract Business Process Logic (ABPL). Abstract Service is a high-level description of the capabilities and categorization of an atomic service with similar functionality. APBL which indicates the order of a collection of activities without the details of execution is to implement the additional function.
Secondly, We focus on an ontology-based Context Model, called CUB-ONT, which derives from a set of descriptive contextual information for sharing common knowledge and logical inference, it includes CUB_SERVICE_ONT and CUB_USER_ONT.
Thirdly, we propose an comprehensive approach for supporting automatic context-aware service discover and selection in a dynamic environment. In order to publish different kind of services and look up services automatically, we extended UDDI to add semantic-based service categorization and service request enhancement as separate layers on top of the UDDI. It is compliant with the universally adopted standard for service discovery. Service communities that are used to organize the large and heterogeneous service space, it also is a distributed and dynamic environment. Therefore, We propose then using multiobjective optimisation techniques to find a set of optimal solutions from which a user can choose the most interesting tradeoff in single service selection or compostion scenarios, namely, CUBSDSA and CUB_CWSDSM. They are both based on Context of mobile user and Qos Attributes of Service. For different type service, we propose a common Service Invocation Model.
In order to verify the feasibility of our proposal, we have developed a preliminary prototype of system components and function that are considered to be critical to the viability of our proposal. At last we conducted serveral experiments in the prototype. Experimental evaluation results demonstrate that the CUB_SDSA algorithm provides a scalable solution to deal with the context-aware service selection problem in single service selection scenarios and CUB CWSDSM approach provides and a flexible solution in the context of composition scenarios. We will make a further step to develop highly automated and dynamically adaptive mobile commerce systems in the future.
引文
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