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为提升大数据环境下准确搜集企业决策支持信息的效率,基于企业决策事务与所需信息类型间有确定映射关系的原理,提出一种基于知识的决策信息需求动态生成方法。发掘决策事务与信息需求间的潜在关联关系并建立知识库,根据动态感知的用户决策事务类型,运用知识实现需求的自动生成和精细描述。实验结果表明,该方法能有效减少信息需求表达的耗时,保证一定准确度,提高决策效率。 相似文献
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邱燕玲 《数字社区&智能家居》2012,(5X):3484-3485
随着企业信息化的发展,人们对异构数据库的需求越来越多,许多信息都需要对异构数据库中的数据进行访问。因此,目前急需一种解决异构数据库信息共享问题的全新解决方案。异构数据库集成技术是实现信息共享的一种方式,最终建立一种统一的接口对数据库进行访问,用户只需指定所需数据即可。该文的研究中,首先通过资料的查阅对传统的异构数据库集成方法进行分析,之后对XML和数据库技术进行了研究和讨论,最后根据研究的结构提出了一种基于XML的B/S构架的异构数据库信息共享方案,异构数据库信息共享技术的研究具有重要的历史意义和市场应用价值。 相似文献
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随着计算机技术的发展,很多企业内部实现了信息的计算机管理,积累了大量的数据.这些数据存在异构现象,相互之间难以集成和共享.传统的数据集成方法已经不能适应企业获取信息的需求,迫切需要一种新的数据集成系统.在XML技术基础上,提出一种基于本体的异构数据集成系统,用来解决数据源之间的语义异构问题.给出一种基于本体的异构数据集成的系统结构,对关键技术问题进行了研究,指出了系统今后研究的方向. 相似文献
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基于模糊多属性决策理论的语义Web 服务组合算法 总被引:5,自引:0,他引:5
综合评估数据异构的服务质量(QoS)从而选择出全局最优的执行计划是语义Web 服务组合研究中的难题之一.提出一种基于模糊多属性决策理论的语义Web 服务组合的优化选择算法(FuMuCom)以解决上述难题.该算法能够评价以实数、区间数和语言型数据描述的QoS 信息,从而进行综合决策.FuMuCom 包括3 个步骤:语言型数据的去模糊化、异构决策矩阵的标准化和QoS 综合评估.同时还介绍了一个可扩展的本体用来描述异构的QoS 数据;同时,从本体进化的角度介绍了一种异构QoS 的聚合算法.最后,通过对真实的服务质量数据进行实验,验证了该算法的优越性和有效性. 相似文献
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针对准则值为灰色异构数据的随机多准则决策问题,提出一种基于核和灰度的灰色随机多准则决策方法.首先给出扩展灰数的灰度和灰色异构数据集的定义;然后,遵循信息充分利用原则,结合灰色异构数据共有的特性,定义灰色异构数据的核向量和灰度向量,进而构造一致性系数几何平面模长排序法和相对折衷距离排序法.实例分析表明了所提出方法的有效性和合理性. 相似文献
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针对军用无线传感器网络中存在大量不同种类的传感器节点,其异构性易形成的信息孤岛问题,通过设计构建通用无线传感器网络信息融合决策平台来屏蔽各类传感器信息在数据结构上的异构性,以实现数据的集成、挖掘,达到信息的实时共享的目的。重点研究设计了平台的数据包解析模块和及其信息融合机制,并使用数据字典作为数据包解析的核心。采用了决策级结构作为平台的信息融合机制,实现了军用传感器网络的信息融合决策。 相似文献
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基于Web服务的电力信息集成系统 总被引:2,自引:0,他引:2
电力信息是包含多种数据模型的典型异构数据库,电力信息的集成对电力系统的运行决策具有重要的意义.文中采用中介器饱装器结构,基于Web服务技术,提出了一种异构信息集成方法.该方法采用GAV方式定义全局模式到局部模式的映射关系,并用关系表来存储映射关系,从而简化了模式映射算法.将该方法应用到电力信息的集成上,实现了电力信息中气象数据、网供负荷数据、电厂负荷数据的集成.实际应用表明,文中所提出的方法可以有效地实现异构信息的集成. 相似文献
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子网拓扑融合技术研究 总被引:1,自引:0,他引:1
针对大规模异构网络的拓扑管理,在对经拓扑发现搜集而来的拓扑信息进行处理,提出了子网拓扑融合概念,阐述了子网拓扑融合在拓扑管理中的地位和作用,分析了子网拓扑融合的需求,研究并建立了基于集合论的子网拓扑融合模型,设计了一种基于XML的子网拓扑融合算法,并通过两个子网拓扑数据检验了该算法的正确性. 相似文献
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为实现航天器质量信息的有效管理和深度应用,分析了航天器质量信息的重要意义和数据特征,充分借鉴当前流程的大数据技术成果,基于ORACLE、MongoDB和HBase技术实现数据源层,基于Hadoop、Storm、MySQL、Berkeley DB和HANA技术实现数据处理层,基于SOA和Web Service技术实现数据服务层,基于多种技术方式实现具有多种应用功能的数据应用层,基于Windows Server 2012、CentOS 6.5、Unix、PHP和HTML5等技术实现系统软件开发部署,建立了覆盖全生命周期全方面的航天器质量信息系统,分析了系统所涉及的多源异构数据的采集、传输与存储,质量信息数据实时处理与分析,实时质量监控、预警和评估等关键技术实现途径,并对应用前景进行了展望,实现航天器研制全周期全过程全方位海量数据采集、处理、分析、预测和评估,使航天器质量管理更加科学、精准、高效。 相似文献
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Regularly updated land cover information at continental or national scales is a requirement for various land management applications as well as biogeochemical and climate modeling exercises. However, monitoring or updating of map products with sufficient spatial detail is currently not widely practiced due to inadequate time-series coverage for most regions of the Earth. Classifications of coarser spatial resolution data can be automatically generated on an annual or finer time scale. However, discrete land cover classifications of such data cannot sufficiently quantify land surface heterogeneity or change. This study presents a methodology for continuous and discrete land cover mapping using moderate spatial resolution time series data sets. The method automatically selects sample data from higher spatial resolution maps and generates multiple decision trees. The leaves of decision trees are interpreted considering the sample distribution of all classes yielding class membership maps, which can be used as estimates for the diversity of classes in a coarse resolution cell. Results are demonstrated for the heterogeneous, small-patch landscape of Germany and the bio-climatically varying landscape of South Africa. Results have overall classification accuracies of 80%. A sensitivity analysis of individual modules of the classification process indicates the importance of appropriately chosen features, sample data balanced among classes, and an appropriate method to combine individual classifications. The comparison of classification results over several years not only indicates the method's consistency, but also its potential to detect land cover changes. 相似文献
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知识图谱是把复杂的领域知识通过数据挖掘、信息处理、知识计量和图形绘制而显示出来,解释知识领域的动态发展规律。知识图谱把所有不同种类的信息(heterogeneous information)连接在一起得到一个关系网络并从"关系"的角度去分析问题。知识图谱目前被广泛应用于智能搜索、智能问答等领域。提出了一种基于知识图谱的智能决策支持框架,用于解决传统决策支持系统存在的问题。通过大数据、知识图谱等海量知识分析和模型构建技术,结合决策支持系统,增强对问题的分解与处理、形成具有关系型网络的知识系统。最后结合电信领域中的经典决策案例,搭建基于知识图谱的欺诈电话智能决策支撑平台。和传统的决策支持系统比较,该研究方法的优点在于结合大数据处理方法提升了知识建模的算力和决策支持的效率,使实时处理大规模信息数据成为现实;基于知识图谱的关系型网络,提升了决策模型的准确性和关联相关性。 相似文献
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This paper proposes an improved decision tree method for web information retrieval with self-map attributes. Our self-map tree has a value of self-map attribute in its internal node, and information based on dissimilarity between a pair of map sequences. Our method selects self-map which exists between data by exhaustive search based on relation and attribute information. Experimental results confirm that our improved method constructs comprehensive and accurate decision tree. Moreover, an example shows that our self-map decision tree is promising for data mining and knowledge discovery. 相似文献
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云计算、大数据等信息技术的应用能够为大量积累的江苏经信数据资源提供存储、共享和分析。按照国家和省级相关要求,建设江苏经信委大数据平台,能够加快政府信息平台整合,消除信息孤岛,为公众、企业和政府的管理与服务建设提供信息资源支撑。 相似文献
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Recently, owing to the capability of mobile and wearable devices to sense daily human activity, human activity recognition (HAR) datasets have become a
large-scale data resource. Due to the heterogeneity and nonlinearly separable nature of the data recorded by these sensors, the datasets generated require
special techniques to accurately predict human activity and mitigate the considerable heterogeneity. Consequently, classic clustering algorithms do not work
well with these data. Hence, kernelization, which converts the data into a new feature vector representation, is performed on nonlinearly separable data.
This study aims to present a robust method to perform HAR data clustering to mitigate heterogeneity in data with minimal resource consumption. Therefore,
we propose a parallel approximated clustering approach to handle the computational cost of big data by addressing noise, heterogeneity, and nonlinearity
in data using data reduction, filtering, and approximated clustering methods on parallel computing environments that have not been previously addressed.
Our key contribution is to treat HAR as big data implemented by approximation kernel K-means approaches and fill the gap between the HAR clustering
cost and parallel computing fields. We implemented our approach on Google cloud on a parallel spark cluster, which helped us to process large-scale HAR
data across multiple machines of clusters. The normalized mutual information is used as validation metric to assess the quality of the clustering algorithm.
Additionally, the precision, recall, f-score metrics values are obtained somehow to compare the results with a classification technique. The experimental
results of our clustering approach prove its effectiveness compared with a classification technique and can efficiently detect physical activity and mitigate
the heterogeneity of the datasets. 相似文献
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Dipl.-Wirtsch.-Ing. Martin Kowalczyk Prof. Dr. Peter Buxmann 《WIRTSCHAFTSINFORMATIK》2014,56(5):289-302
Data-centric approaches such as big data and related approaches from business intelligence and analytics (BI&A) have recently attracted major attention due to their promises of huge improvements in organizational performance based on new business insights and improved decision making. Incorporating data-centric approaches into organizational decision processes is challenging, even more so with big data, and it is not self-evident that the expected benefits will be realized. Previous studies have identified the lack of a research focus on the context of decision processes in data-centric approaches. By using a multiple case study approach, the paper investigates different types of BI&A-supported decision processes, and makes three major contributions. First, it shows how different facets of big data and information processing mechanism compositions are utilized in different types of BI&A-supported decision processes. Second, the paper contributes to information processing theory by providing new insights about organizational information processing mechanisms and their complementary relationship to data-centric mechanisms. Third, it demonstrates how information processing theory can be applied to assess the dynamics of mechanism composition across different types of decisions. Finally, the study’s implications for theory and practice are discussed. 相似文献