共查询到20条相似文献,搜索用时 140 毫秒
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基于本体的供应链信息交换研究 总被引:3,自引:0,他引:3
文章介绍供应链成员之间的信息交换是供应链集成的核心问题,基于EDI标准和XML标准的信息交换虽然解决了语法层次上的互操作性,但在解决语义层次的互操作性上存在不足,文中针对供应链信息交换模式进行了分析,提出基于本体的供应链信息交换模式,解决语义层次上的互操作性问题。 相似文献
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为了解决信息集成中的语义异构问题,引入本体技术,借鉴“Mediator/Wrapper”体系结构,结合混合本体以及Web Servioes技术,提出了分布式网络环境下的基于本体的信息集成框架,阐述了如何利用本体技术解决语义异构问题,给出了框架的层次结构以及关键技术,包括本体构建、查询处理和服务注册中心,然后利用原型系统验证了框架是可行的。该框.架解决了信息集成中的语义异构问题。 相似文献
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要解决寻呼台合并后用户BP机的改频问题,可以从寻呼网络的后端入手,通过信息分流的方法,按地址码将寻呼信息送往不同的编码器及发射机,从而解决了问题。本文给出了寻呼系统信息分流器的设计原理及方法,并对软件的设计难点给出源程序 相似文献
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研究了工业控制网络的实时应用特性,建立周期信息和非周期信息发送优先级的模糊控制模型,并提出了一种新的实时信息调度方法。分析了信息调度的实时性和总线的利用效率,并与典型的现场总线实时能力作了比较,分析说明了基于模糊控制的实时任务调度策略(FCSS)较好地解决了周期信息和非周期信息的实时发送问题,可以有效解决控制网络实时信息的传输和总线资源利用率之间的矛盾。 相似文献
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中文信息导航系统的关键软件技术分析 总被引:4,自引:0,他引:4
信息导航系统的设计与开发涉及广泛的技术问题。介绍了信息导航系统的特点和现状以及信息导行系统的总体设计,并主要就大规模中文信息导航系统设计中的关键软件技术进行了讨论,包括搜索引擎Robot、中文信息处理系统和导航系统相关服务的设计及其需要解决的主要技术问题,并提供了相应问题的解决方法。最后,简要提到了导航系统设计中需要解决的主要硬件技术问题。 相似文献
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信息集成作为CIMS实现系统集成的基础,具有十分重要的作用和地位。本文介绍了信息集成的一般结构和目标,提出了解决信息集成的一般方法,并给出实际应用系统中的信息集成模型。 相似文献
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常其刚 《数字社区&智能家居》2007,(4):38-39
当今社会,面对浩如烟海的Internet信息和来自企业内外众多的访问请求,有效地组织和规划内部网信息资源,以达到减轻服务器的负担、降低访问费用、提高Internet网使用效率等成为必须解决的问题。本文介绍了互联网通信技术的特点、应用和发展,提出了一些新的方法,解决了互联网通信过程中的信息访问资源浪费、信息阻塞和信道负担增加的问题。 相似文献
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Wizard: a database inference analysis and detection system 总被引:1,自引:0,他引:1
The database inference problem is a well-known problem in database security and information system security in general. In order to prevent an adversary from inferring classified information from combinations of unclassified information, a database inference analyst must be able to detect and prevent possible inferences. Detecting database inference problems at database design time provides great power in reducing problems over the lifetime of a database. We have developed and constructed a system called Wizard to analyze databases for their inference problems. The system takes as input a database schema, its constituent instances (if available) and additional human-supplied domain information, and provides a set of associations between entities and/or activities that can be grouped by their potential severity of inference vulnerability. A knowledge acquisition process called microanalysis permits semantic knowledge of a database to be incorporated into the analysis using conceptual graphs. These graphs are then analyzed with respect to inference-relevant domains we call facets using tools we have developed. We can determine inference problems within single facets as well as some inference problems between two or more facets. The architecture of the system is meant to be general so that further refinements of inference information subdomains can be easily incorporated into the system 相似文献
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Multistage fuzzy inference, where in the consequence in an inference stage is passed to the next stage as a fact, is studied and formulated as a type of linguistic-truth-value propagation, based on a concept of linguistic similarities between conditional propositions in successive stages. The formulation is useful in studying the characteristics of multistage fuzzy inference and reveals its structural relationship to multilayer perceptrons. The learning algorithm for multistage fuzzy inference is then derived, using backpropagating error information. The algorithm provides a means of automatically training the multistage fuzzy inference network, using input-output exemplar patterns. Intermediate membership functions based on simulation results, which are generated automatically in the intermediate stage, are proposed. The intermediate stage fuzzy-classifies the input space using intermediate membership functions. In this way, intermediate membership functions provide information regarding regional characteristics in exemplar patterns 相似文献
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Harabagiu S.M. Moldovan D.I. 《Parallel and Distributed Systems, IEEE Transactions on》1998,9(8):729-747
This paper presents a possible solution for the text inference problem-extracting information unstated in a text, but implied. Text inference is central to natural language applications such as information extraction and dissemination, text understanding, summarization, and translation. Our solution takes advantage of a semantic English dictionary available in electronic form that provides the basis for the development of a large linguistic knowledge base. The inference algorithm consists of a set of highly parallel search methods that, when applied to the knowledge base, find contexts in which sentences are interpreted. These contexts reveal information relevant to the text. Implementation, results, and parallelism analysis are discussed 相似文献
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如今微博和Twitter等社交网络平台被广泛地用于交流、创建在线社区并进行社交活动。用户所发布的内容可以被推理出大量隐私信息,这导致社交网络中针对用户的隐私推理技术的兴起。利用用户的文本内容及在线行为等知识可以对用户进行推理攻击,社交关系推理和属性推理是对社交网络用户隐私的两种基本攻击。针对推理攻击保护机制和方法的研究也在日益增加,对隐私推理和保护技术相关的研究和文献进行了分类并总结,最后进行了探讨和展望。 相似文献
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Malicious users can exploit the correlation among data to infer sensitive information from a series of seemingly innocuous data accesses. Thus, we develop an inference violation detection system to protect sensitive data content. Based on data dependency, database schema and semantic knowledge, we constructed a semantic inference model (SIM) that represents the possible inference channels from any attribute to the pre-assigned sensitive attributes. The SIM is then instantiated to a semantic inference graph (SIG) for query-time inference violation detection. For a single user case, when a user poses a query, the detection system will examine his/her past query log and calculate the probability of inferring sensitive information. The query request will be denied if the inference probability exceeds the prespecified threshold. For multi-user cases, the users may share their query answers to increase the inference probability. Therefore, we develop a model to evaluate collaborative inference based on the query sequences of collaborators and their task-sensitive collaboration levels. Experimental studies reveal that information authoritativeness, communication fidelity and honesty in collaboration are three key factors that affect the level of achievable collaboration. An example is given to illustrate the use of the proposed technique to prevent multiple collaborative users from deriving sensitive information via inference. 相似文献
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目前自然语言推理(Natural language inference,NLI)模型存在严重依赖词信息进行推理的现象.虽然词相关的判别信息在推理中占有重要的地位,但是推理模型更应该去关注连续文本的内在含义和语言的表达,通过整体把握句子含义进行推理,而不是仅仅根据个别词之间的对立或相似关系进行浅层推理.另外,传统有监督学习方法使得模型过分依赖于训练集的语言先验,而缺乏对语言逻辑的理解.为了显式地强调句子序列编码学习的重要性,并降低语言偏置的影响,本文提出一种基于对抗正则化的自然语言推理方法.该方法首先引入一个基于词编码的推理模型,该模型以标准推理模型中的词编码作为输入,并且只有利用语言偏置才能推理成功;再通过两个模型间的对抗训练,避免标准推理模型过多依赖语言偏置.在SNLI和Breaking-NLI两个公开的标准数据集上进行实验,该方法在SNLI数据集已有的基于句子嵌入的推理模型中达到最佳性能,在测试集上取得了87.60%的准确率;并且在Breaking-NLI数据集上也取得了目前公开的最佳结果. 相似文献
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Recommendation is an important application that is employed on the Web. In this paper, we propose a method for recommending items to a user by extending a probabilistic inference model in information retrieval. We regard the user’s preference as the query, an item as a document, and explicit and implicit factors as index terms. Additional information sources can be added to the probabilistic inference model, particularly belief networks. The proposed method also uses the belief network model to recommend items by combining expert information. Experimental results on real-world data sets show that the proposed method can improve recommendation effectiveness. 相似文献