Mobile Web Middleware of NFC Context-Awareness Applications

With the development of wireless networks and mobile computing, more advanced applications with context-awareness and adaptability to their changing context are needed. However, building context-aware applications is difficult due to the lack of adequate infrastructure support. In this paper, a web middleware architecture for the development of context-awareness applications using near field communication （NFC） is proposed. Based on it, the efficient support for acquiring, interpreting, and accessing context is provided, and the user＇s quality of experience is improved. Moreover, a mobile web middleware for the testing and full realization of NFC context-awareness applications has been developed together with two application examples.

Reducing semantic bias of annotations for semantic web service discovery

In order to improve the effectiveness of semantic web service discovery, the semantic bias between an interface parameter and an annotation is reduced by extracting semantic restrictions for the annotation from the description context and generating refined semantic annotations, and then the semantics of the web service is refined. These restrictions are dynamically extracted from the parsing tree of the description text, with the guide of the restriction template extracted from the ontology definition. New semantic annotations are then generated by combining the original concept with the restrictions and represented via refined concept expressions. In addition, a novel semantic similarity measure for refined concept expressions is proposed for semantic web service discovery. Experimental results show that the matchmaker based on this method can improve the average precision of discovery and exhibit low computational complexity. Reducing the semantic bias by utilizing restriction information of annotations can refine the semantics of the web service and improve the discovery effectiveness.

A Context-Aware Approach for the Spatial Data Infrastructure Portal

The infrastructure of most of the practical and construction activity in communities is based on correct understanding and proper use of spatial data in GIS1?and SDI2. Optimal and efficient use of infrastructure systems of the spatial data by users, depends on how to search and access of user to proper and desired data among informative sources of various organizations. Search operation and access of users to various information of multiple sources located on Spatial Data Infrastructure Network is confusing and time-consuming due to diversity and relatively high volume of spatial information. Because there are numerous classes and subclasses of various complications on the pattern of SDI, unaware user to the pattern may be confused in select displaying the proper spatial layer. In optimum condition, the user should have access to the appropriate data type based on his status and task and environmental conditions. Making intelligent Graphical User Interface by inference based on task information user and his expertise, the appropriate information and consistent with conditions will be achieved. Selecting and displaying of spatial layers related to the technical-organizational approach of system user provides him special assistance both in terms of filtering the irrelevant data and speed of operation in access optimal information than non-selective displaying state. For this purpose, designing and employment context-aware techniques in servicing user interface of system based on recognition of the technical expertise of the user can be a good solution in data adaptive displaying and context-aware servicing to users.

面向功能语义增强与标签关联的Web服务标签推荐

为了提升标签推荐的质量,提出一种面向功能语义增强与标签关联的Web服务标签推荐方法。将语境权重融入TextRank模型,提取与服务功能契合度高的关键词,用于构建功能语义增强的服务表征向量;建立标签关联图,基于改进的GraphSAGE模型生成标签关联向量;利用KNN算法获取推荐的主标签与候选标签集合,面向服务表征向量和标签关联向量构建融合适配度与关联度的标签推荐方法。实验表明,所提方法在accuracy与F_(1)-score指标上优于当前流行的标签推荐方法,标签推荐质量得到提升。

Context-driven reconciliation in ontology integration

In order to solve the semantic irreconcilable problems caused by contextual differences during the process of ontology integration, a context-driven reconciliation mechanism is proposed. The mechanism is based on the previous work about a context-based formalism-Context-SHOIQ （D ＋ ） DL, which is used for explicitly representing context of ontology by adopting the description logic and the category theory. The formalism is extended by adding four migration rules （InclusionRule, SelectionRule, PreferenceRule, and MappingRule）, that are used to specify what should be imported into the IntegrativeContext, and three related contextual integration operations of increasing interoperability （import, partial reconciliation, and full reconciliation）. While not exhaustive, the mechanism is sufficient for solving the five types of semantic irreconcilable problems that are discussed, and favors integration of ontologies from one context to another.

Context query and association discovery for collaborative environment

A context memory model and an approach for context query and association discovery are proposed. The context query is based on a resource description framework （RDF） dataset and SPARQL language. To discover collaborative associations, an approach of transforming RDF named graphs into ＂context graph＂ is proposed. First, the definitions of the importance of the nodes and the weight assignment for the ＂context graph＂ are given. Secondly, the implementation of a spread activation algorithm based on ＂context graph＂ is proposed. An infrastructure is also built up in the collaborative context space （CCS） system to support context memory and knowledge discovery in a collaborative environment.

Context-Aware技术在智能网络课程设计中的应用

Context-aware具有自组织性、自适应性和自反馈性,智能网络课程的设计与开发要求教育学、心理学理论和先进的计算机算法的融合.从分析Context-aware技术及其特点入手,将Context-aware应用于网络课程来改变课程教学模式和学生学习方式,提高网络课程的智能化程度及学生的学习效率.

Normalized MEDLINE Distance in Context-Aware Life Science Literature Searches

Literature searches on the Web result in great volumes of query results. A model is presented here to refine the search process using user interests. User interests are analyzed to calculate semantic similarity among the interest terms to refine the query. Traditional general purpose similarity measures may not always fit a domain specific context. This paper presents a similarity method for medical literature searches based on the biomedical literature knowledge source ＂MEDLINE＂, the normalized MEDLINE distance, to more reasonably reflect the relevance between medical terms. This measure gives more accurate user interest descriptions through calculating the similarities of user interest terms to rerank the interest term list. The accurate user interest descriptions can be used for query refinement in keyword searches to give more personalized results for the user. This measure also improves the search results for personalization through controlling the return number of results on each topic of interest.

一种基于结构感知的肝血管分割模型

为了在缺乏大量肝血管标注信息的情况下增强肝血管结构分割,提出了局部-长距离-相邻信息融合模块,并将其嵌入U-Net的编码阶段,得到一种基于结构感知的肝血管分割网络。该模块有3个分支:提取特征图局部信息的残差卷积模块,利用自注意力机制提取特征图的全局信息的长距离提取模块,以及利用相邻切片补充上下文信息的相邻信息提取模块。通过将以上3个分支模块的输出特征图进行融合,可以有效提升网络的血管结构感知能力,缓解2D网络无法表征血管立体走向与3D网络训练数据不足的问题。分别在MICCAI十项全能数据集中的肝血管与肿瘤数据集和三甲医院收集标注的自采肝血管数据集上进行了广泛的对比实验。结果表明,与多种主流的分割算法相比,该算法取得了最优的血管分割性能。所提出的方法在MICCAI数据集上Dice值达到64.04%,在自采肝血管数据集上Dice值达到了72.07%。

情景感知的物流Web服务动态优化组合研究

第四方物流服务通过大规模的资源整合,可以将领域内优秀的物流服务组合起来,为用户提供技术、仓储、运输服务等最佳结合的物流服务方案,实现物流服务的低成本、高效率、实时运作。然而,如何高效、动态地构建满足用户服务质量需求的可靠物流服务组合,是第四方物流服务商亟需解决的关键问题。针对这一问题,提出了一种情景感知的物流Web服务动态组合方法,该方法首先基于改进的遗传算法,将用户提出的全局QoS约束分解成局部QoS约束,从而将QoS感知的物流Web服务组合这一全局优化问题转化成局部最优服务选择问题;然后,在物流服务流程执行的过程中,依据当前关键的情景信息,选出可用并且能够满足局部QoS约束的最优物流服务;最后,通过实验验证了所设计方法的可行性和有效性。

基于语义Web的农业生产协同决策服务机制研究

针对分布式农业知识资源异构、自治和难以实现共享服务的问题,采用语义Web技术,提出了基于Web本体建模语言的异构农业知识资源描述模型和决策服务形式化表达模型。以模型为基础,将农业协同决策服务需求分解为多个决策流程片段,设计了基于上下文感知计算的农业问题协同决策服务机制,实现对多个决策流程任务和知识资源的按需调度,提高了农业知识资源的利用效率和协同推理效率。与其他方案不同,该机制进一步考虑了任务均衡分解与知识资源智能调度对协同决策服务机制的影响,并通过生猪疾病协同诊断决策系统的搭建进行了应用实例验证。实验表明,该方法在求解精度、决策效率方面优于传统农业智能决策方法。

无线Web访问的缓存和预取机制

缓存和预取在提高无线环境下的Web访问性能方面发挥着重要作用。文章研究针对无线局域网的Web缓存和预取机制,分别基于数据挖掘和信息论提出了采用序列挖掘和延迟更新的预测算法,设计了上下文感知的预取算法和获益驱动的缓存替换机制,上述算法已在Web缓存系统OnceEasyCache中实现。性能评估实验结果表明,上述算法的集成能有效地提高缓存命中率和延迟节省率。

群体Pareto最优的Web服务组合决策方法

针对异构数据描述的QoS信息和群体中个性化的用户Qos偏好的Web服务组合问题，提出了一种基于多属性决策（MADM）理论的面向群体用户的语义web服务选择算法（GUWSSA），GUWSSA能够获得群体Pareto最优服务组合计划。首先定义了能够描述群组的用户上下文本体和支持异构数据类型的服务上下文本体，然后给出了GUWSSA的详细细节，包括异构决策矩阵的规格化、综合评价、获得群体Pareto最优方案，最后通过一系列实验验证了该算法的性能和有效性。实验数据表明，在用户QoS偏好不同和Qos数据类型异构的情况下，GUWSSA能够选出群体Pareto最优的服务组合计划。

基于上下文感知进程网络的Web服务组合方法

针对Web服务组合的个性化问题,提出一种基于上下文感知进程网络的Web服务组合方法,支持上下文感知组合系统的高层建模与系统的底层实现。采用CCS进程代数和标签转换系统,描述上下文感知组合模型的形式化语义,给出上下文感知系统模型的实现框架。分析结果证明了该组合方法的可行性。

任务计算中基于语义Web的上下文感知服务选择

针对普适环境中任务计算的特点,分析了任务计算的层次结构和复杂任务的分解策略,设计了一种任务计算中服务发现的体系结构。此体系结构依赖于服务和内容的语义表示,而这种语义表示是基于本体的、共享的。它不仅可以增强精确度和调用率,而且能够实现知识共享、基于能力的搜索、自主推理以及语义匹配等功能。据此,提出了一种基于语义Web的上下文感知动态服务选择机制,这种机制可以根据待匹配的服务的动态上下文属性来对其进行过滤和排序,从而进一步优化了发现的过程、节约了用户的时间和精力。此外,该选择机制可用于发现有用的静态或动态上下文信息,从而为用户提供最合适、最相关的服务。

基于指控交互信息用户语境的语义Web服务发现和组合

在军事指挥控制模拟训练系统和训练装备研究领域,指控系统与仿真系统的开发是相对的,遵循不同的标准和协议,在结构和功能上存在很大的差异。通过建立指控交互信息的语义Web服务概念参考模型,提出指控系统与仿真系统互操作性面临的技术需求,研究基于指控交互信息用户语境的语义Web服务发现和服务组合,提出了基于静态与动态用户语境匹配的语义Web服务发现架构和服务匹配算法,以及基于用户语境的语义Web服务组合算法。

Web语境敏感页面分层设计实现方法

语境context也称为上下文。针对Web语境敏感页面设计的复杂性问题,遵循EVP原则并借鉴COP,提出一种面向语境风格(COS,Context-Oriented Style)的页面分层语法。给出COS页面转换框架并说明其工作原理。区别于COP语言,COS在当前Web页面标签语言基础上设计了一种层槽语法,采用四元组来描述页面元素的变化,并设计实现一个解释器来实施变化。不同于传统的以元素为中心的页面描述方式,COS特点是语境条件为中心。通过实例验证COS方案简单有效,并具有语境变化适应性,同时增强安全控制的可验证性。

基于历史用户QoS感知的Web服务发现方法

目前的Web服务发现方法,由于没有充分利用用户情境信息,导致在服务发现时间和结果准确率方面存在不足。首先对包括当前用户在内的情境相似的用户进行了聚类,缩小了服务发现的范围;然后,在此基础上利用当前用户偏好信息及情境相似的历史用户感知到的候选服务的QoS数据,给出了一种基于历史用户QoS感知的Web服务发现方法,包括候选服务的QoS数据获取和综合权重计算;最后,结合实验并与其他Web服务发现方法进行比较,证明了该方法在服务发现结果的准确率和时间效率方面均有了一定的提升。

基于语义Web技术的上下文感知的智能移动服务

语义Web技术应用于上下文感知的智能移动服务,通过构建上下文信息本体,使得移动服务的实体之间可以进行上下文信息共享和语义互操作,并进行上下文信息推理,实现智能服务。本文首先介绍了语义Web及本体技术。其次阐述了语义Web技术应用于上下文感知的移动服务,然后详细分析了智能移动服务中的上下文信息本体构建,包括通用的上下文信息本体、用户概况本体、情境本体以及服务本体等,接着介绍了相关的研究项目,最后进行展望和总结。

基于AO4BPEL含感知上下文的Web服务组合模型的研究

Web服务已经成为了一种集成Internet上分布的不同类型的应用以提供增值服务的通用技术。文章基于面向切面的横切关注点动态编织技术,提出了一种含有感知上下文插件的面向切面的Web服务组合模型,使得Web服务组合更具用户化和动态适应性;并通过实例证明了该模型的有效性。