基于用户满意度的学习服务发现算法

针对用户对e-Learning服务发现系统提供的服务不满意或者满意程度不稳定的问题,引入了用户满意度因子,设计了一个学习服务发现算法--eLSDAUS.该算法允许用户参与服务发现的过程,对服务发现的效果进行评价,学习服务发现系统把用户的评价反馈到学习服务发现算法,利用修正函数修正更新发布服务各属性的匹配度权值,优化反馈给用户的综合匹配度的计算,实验表明,在发布的学习服务数量超过1万时,该算法能够提高服务发现的查准率3%,而且随着发布服务数量的增多,效果会更好,经过127天的学习,用户对服务发现结果的总体满意比率可超过93%.     

基于服务质量反馈的语义Web服务匹配算法

传统Web服务框架不支持基于服务质量(QoS)的查询,不能满足用户对服务性能的要求。针对该问题,通过建立QoS本体,提出基于服务功能和QoS的两阶段服务匹配算法。在此基础上设计一种基于用户反馈的服务质量算法,根据发布和反馈的QoS,综合评价服务的质量。实验结果表明,该算法能提高查准率,改善服务发现的性能。     

基于社会网络动态反馈的Web服务信任度计算

在当前服务计算背景下,针对用户难以获得满足需求的可信服务问题,提出基于社会网络动态反馈的Web服务信任度模型.基于用户使用经验设计服务直接信任度算法,对服务交易情况进行动态跟踪和监测.当用户缺乏使用某服务的直接经验时,基于社会网络中服务使用者信任度,聚合其他服务使用者对服务的直接信任度,计算该服务的间接信任度.采用修正因子进行修正,以提高社会网络节点及关联服务可信性.算法分析表明,该方法是可行和有效的.     

一种支持QoS的自适应Web服务发现模型

服务质量是Web服务发现中的关键问题.该文提出一种支持QoS的自适应Web服务发现模型,在满足用户对Web服务功能需求的基础上,依据QoS等非功能性指标对Web服务进行选择和排序,并给出服务的选择排序算法,该算法以服务注册参数、用户反馈信息和实时监测数据为依据,能动态地对服务的非功能性指标进行评价,返回最合适的服务给用户.实验证明,该模型有效地提高了系统的可用性.     

一种基于Skyline的服务选择方法

随着网络上各种web服务数量的急剧增长,如何发现满足用户功能性和非功能性需求的服务成为亟待解决的关键问题.根据用户确定的功能和非功能性需求,充分利用Skyline方法中的实例间支配关系,首先对网络上各种服务从功能层次进行筛选,然后从QoS层次对选择的服务实现进一步的筛选,从而选择出两者都较优的暇务.该方法对输入,输出匹配度高的服务分别进行考虑,并进行组合判断来查找满足用户需求的原子服务和组合服务.给出了相应的服务发现算法,且通过仿真实验来验证分析所提出方法的可行性和有效性.     

基于服务质量信息的服务组装算法

现有的服务组装方法不能根据用户的实际需求对服务构件进行选择和组装。针对该问题,提出一种基于服务质量信息的服务组装算法。定义服务接口间的匹配度,引入服务质量信息,把服务间的匹配度转变为有向图中边的权重,从而将服务构件的组装问题转化为寻找有向图中的最短路径问题。实例分析结果证明了该算法的有效性。     

基于对等网的Web服务发布和发现机制研究

传统的Web服务发布和发现机制在效率、可靠性、安全等方面存在一定缺陷,提出了一种基于对等网技术的Web服务发布和发现新机制.该机制利用对等体服务发布技术实现了Web服务的快速和即时发布,利用对等网通告发现策略实现了Web服务的高效搜索和定位.同时给出了在JXTA对等网络中即时发布和异步发现Web服务的算法实现.研究表明,该机制有助于普及网络边缘服务,增强应用的服务能力,是一种效率更高的分布式动态发布和发现Web服务的新机制.     

改进的语义Web服务匹配算法设计与实现

引用领域本体对Web服务进行语义描述,再进行语义层上的匹配,是Web服务匹配研究领域的重要研究方向。针对传统匹配算法在语义Web服务发现中的不足,采用语义距离、匹配度系数等对其进行扩展,在此基础上实现一个原型系统。实验表明,该算法能提高Web服务的匹配精度。     

支持QoS约束的语义Web服务发现模型

分析了现有Web服务发现的不足,在系统研究Web服务发现框架的基础上,将QoS模块引入,提出一个支持QoS约束的语义Web服务发现模型SWSDM-QoS.在该模型中,支持QoS的服务发布,查找和反馈,并在此基础上提出一个基于QoS约束的服务选择算法.已经基于Microsoft.NET平台实现了一个原型系统.     

基于本体和二部图的网格服务发现算法研究

为了提高网格服务发现的查全率、查准率和效率,论文设计了一个基于本体和二部图的网格服务发现算法OGSDA-BG。该算法把请求服务和发布服务的属性集分别作为二部图顶点集,所有匹配属性之间的连线为边,边权是属性匹配度,把问题转换为二部图的最优完全匹配。实验结果表明该算法的查全率和查准率较以前的算法提高了10%~50%,尽管服务发现的效率降低10%左右,但是在可接受范围之内。     

Assessing e-learning 2.0 system success

Traditional e-learning systems support “one-way” communication. Teachers provide knowledge for learners, but they are unable to use a student’s learning experiences to benefit the class as a whole. To address these problems, this study explores e-learning success factors via the design and evaluation of an e-learning 2.0 system. This study develops a theoretical model to assess user satisfaction and loyalty intentions to an e-learning system using communication quality, information quality, system quality, and service quality. The empirical results show that communication quality, information quality, and service quality significantly and positively affect user satisfaction and loyalty intentions to use the e-learning system for sharing experience, communicating with others, and getting feedback.     

一种基于QoS的网格服务选择机制

开放网格服务体系结构OGSA提出了网格服务的概念,为网格资源的虚拟化管理给出了一条有效途径。当前网格系统对于网格服务的支持主要集中在服务的功能发现与调用部分,缺乏对服务的非功能属性的管理支持。服务的非功能属性如服务的响应时间、价格、可靠性等对于用户来说非常重要,体现着用户对网格服务的QoS需求。基于QoS的服务选择机制能够对网格服务的QoS模型进行管理和度量,对于用户提出的QoS需求,服务匹配算法能够为用户选择满足需求倾向的服务。     

Fuzzy ontologies-based user profiles applied to enhance e-learning activities

Nowadays, the impact of technological developments on improving human activities is becoming more evident. In e-learning, this situation is no different. There are common to use systems that assist the daily activities of students and teachers. Typically, e-learning recommender systems are focused on students; however, teachers can also benefit from these type of tools. A recommender system can propose actions and resources that facilitate teaching activities like structuring learning strategies. In any case, a complete user’s representation is required. This paper shows how a fuzzy ontology can be used to represent user profiles into a recommender engine and enhances the user’s activities into e-learning environments. A fuzzy ontology is an extension of domain ontologies for solving the problems of uncertainty in sharing and reusing knowledge on the Semantic Web. The user profile is built from learning objects published by the user himself into a learning object repository. The initial experiment confirms that the automatically obtained fuzzy ontology is a good representation of the user’s preferences. The experiment results also indicate that the presented approach is useful and warrants further research in recommending and retrieval information.     

一种基于情景感知的学习服务发现算法

化学计算模型是基于化学反应和计算之间比喻的并行计算模型,其内在的并行性及不确定性可以有效地消除与计算逻辑本身无关的人为顺序性,从而能够以更为直观和抽象的方式来描述并行计算。但也正是由于其内在的并行性和高层抽象性,使得特定的控制机制难以描述。高阶化学编程语言是对传统化学计算模型的扩展和泛化,在保留传统化学计算特征的同时,不仅可以有效地描述传统的控制机制,也可以方便地定义新的控制机制。通过从简单面向对象语言到高阶化学语言的转换,给出了面向对象语言的一种化学语义描述,提供了一种描述面向对象系统的新视角,也为结合面向对象编程和化学编程提供了一种可能。     

一种用户需求驱动的服务资源建模方法

面向用户需求通过松散耦合的服务资源的重用和重组,实现其按需发现与组合,正成为网络化软件主流的开发范型。如何对服务进行建模已成为这种范型中的一个重要问题。提出一种用户需求驱动、基于RGPS(Role-Goal-Process-Service)领域资产的服务建模方法。通过对服务模型进行语义需求封装来满足用户需求,从而实现用户需求和服务之间的动态"握手"。该方法已在原型系统中得以应用和验证。     

A service composition approach based on sequence mining for migrating e-learning legacy system to SOA

With the fast development of business logic and information technology, today's best solutions are tomorrow's legacy systems. In China, the situation in the education domain follows the same path. Currently, there exists a number of e-learning legacy assets with accumulated practical business experience, such as program resource, usage behaviour data resource, and so on. In order to use these legacy assets adequately and efficiently, we should not only utilize the explicit assets but also discover the hidden assets. The usage behaviour data resource is the set of practical operation sequences requested by all users. The hidden patterns in this data resource will provide users' practical experiences, which can benefit the service composition in service-oriented architecture (SOA) migration. Namely, these discovered patterns will be the candidate composite services (coarse-grained) in SOA systems. Although data mining techniques have been used for software engineering tasks, little is known about how they can be used for service composition of migrating an e-learning legacy system (MELS) to SOA. In this paper, we propose a service composition approach based on sequence mining techniques for MELS. Composite services found by this approach will be the complementation of business logic analysis results of MELS. The core of this approach is to develop an appropriate sequence mining algorithm for mining related data collected from an e-learning legacy system. According to the features of execution trace data on usage behaviour from this e-learning legacy system and needs of further pattern analysis, we propose a sequential mining algorithm to mine this kind of data of the legacy system. For validation, this approach has been applied to the corresponding real data, which was collected from the e-learning legacy system; meanwhile, some investigation questionnaires were set up to collect satisfaction data. The investigation result is 90% the same with the result obtained through our approach.     

基于用户请求服务的QoS评价模型

进行SOA系统构建时,在选择同一功能服务不同物理实现的过程中,需要考虑用户适合度。提出根据用户需求确定服务QoS属性集的方法,该方法用扩展的WSDL协议描述服务QoS,量化服务QoS和用户QoS需求。构建基于用户请求的服务质量模型和相应算法,完成对最佳用户适合度服务物理实现的选择。     

A target advertisement system based on TV viewer’s profile reasoning

The traditional broadcasting services such as terrestrial, satellite and cable broadcasting have been unidirectional mass media regardless of TV viewer’s preferences. Recently rich media streaming has become possible via the broadband networks. Furthermore, since bidirectional communication is possible, personalcasting such as personalized streaming service has been emerging by taking into account the user’s preference on content genres, viewing times and actors/actresses etc. Accordingly personal media becomes an important means for content provision service in addition to the traditional broadcasting service as mass media. In this paper, we introduce a user profile reasoning method for TV viewers. The user profile reasoning is made in terms of genre preference and TV viewing times for TV viewer’s groups in different genders and ages. For user profiling reasoning, the TV viewing history data is used to train the proposed user profiling reasoning algorithm which allows for target advertisement for different age/gender groups. To show the effectiveness of our proposed user profile reasoning method, we present plenty of the experimental results by using real TV usage history.     

情景感知的P2P移动社交网络构造及发现算法

如何通过情景感知,获得用户的行为特征,从而自动发现潜在的社会关系,是移动社交网络重要的研究内容之一.该文提出了情景感知的移动P2P社交网络系统架构、聚合模型及发现算法,将用户的位置信息、环境特征、运动轨迹等引入到聚合算法中,智能地聚合成潜在的P2P社交网络,根据用户需求自主发现匹配的社会关系,避免了社交活动的盲目性和随意性.最后对该方案和算法进行了理论分析及实验验证,结果表明该文所提出的方案和算法具有较高的响应速度、准确率及用户满意度.     

Developing a model to assess the success of e-learning systems: evidence from a manufacturing company in transitional economy

This paper examines the success of an e-learning system in a company from the perspective of employees by using a multimethod approach. For this purpose Moodle learning management system was used. The success of e-learning as an information system was evaluated using four constructs of the updated DeLone and McLean IS success model—system quality, use, user satisfaction and net benefits, and adding one more construct—user performance. In this research a combination of observation and survey as two different research methods was used, which allowed the new measure to be incorporated into the model. Empirical assessment was carried out by exploratory factor analysis, confirmatory factor analysis and structural equation modeling. The research model was found to be valid and reliable. The results provide an expanded understanding of the constructs that measure the success of an e-learning system, helping to more deeply understand the key success dimensions and their interrelationships. The implications of our work were discussed. The DeLone and McLean IS success model applied equally well. However, the use of observation as a method of data collection revealed the weaknesses of the original model.