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本文叙述了银行客户条形码自动查询系统的硬、软件结构,并说明了该系统的功能特点、应用情况及前景。 相似文献
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针对高校师生知识的分布式、动态性和异构性等特点以及高校知识的学科专业的分类特征,提出了一种基于本体的高校知识管理系统模型OUKM,重点研究了OUKM的知识组织、知识查询和知识排序等实现方法,提出了基于知识结构本体的知识组织方法,以及精确知识查询、排序算法和模糊知识查询、排序算法。针对计算机专业知识,实现了一个基于本体的高校知识管理系统。 相似文献
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查询扩展是优化信息检索的一种有效方法。基于关键词的查询扩展对语义信息的忽略为结果带来了不好的影响,因而提出一种基于本体的查询扩展方法。首先建立本体模型,通过计算本体中的概念语义相似度和实例语义相似度,实现语义查询扩展。 相似文献
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为了解决电力客户知识共享和语义互操作问题,利用本体工具以一种无歧义的方式建立了电力客户的特征模型,并利用本体标准语言OWL进行形式化描述,为建立基于本体的电力客户知识库模型奠定了基础. 相似文献
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针对目前基于关系型数据库等存储模式的本体存储查询效率较低的情况,提出使用XML数据库BaseX进行本体的存储,并设计了相应的本体存储查询架构。在对BaseX存储结构与接口的研究基础上,实现对OWL本体的存储。利用BaseX的查询接口和XQuery查询语言对OWL本体进行检索,在建立推理规则库基础上,实现本体查询扩展与推理。实验将提出的存储查询方法与基于关系型数据库的存储查询方法进行对比,验证了提出的方法具备高效的存储查询性能,同时具备本体查询的推理能力。 相似文献
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半结构化数据库没有固定的库模式,用户对其结构难以产生清晰的认识,从而无法有效地查询所需的内容.提出了一种基于本体的柔性查询,用户通过了解数据库本体语义信息而发出的查询不必遵循严格的数据库模式也能得出结果.由于在半结构化数据库上直接查找效率很低,故在其上生成描述结构模式的概念本体库.查询模块先在本体库上评估能否得出查询结果,再在数据库上执行查询.然而由于本体库可能是图的形式,其查询代价仍然很高,本质上是NP问题,进一步研究了将图转化为树的方法,并给出了相应的算法. 相似文献
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Semantic integration, which can be divided into three parts including ontology mapping, mapping representation, and reasoning and query rewriting with mappings, plays a key role in information integration systems. This paper develops an XML query rewriting and ontology integration mechanism, which acts as a global-as-view (GAV) approach to represent and query semantic information in mediator based information integration environment. It proposes the patterns and properties of ontology mappings, discusses the procedure and algorithm of ontology integration firstly, and then proposes the ontology based XML query mechanism, especially the XML query rewriting mechanism. Finally, a mediator-based implementation of the mechanism in OBSA system is introduced. 相似文献
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基于遗传算法的顾客购买行为特征提取 总被引:2,自引:0,他引:2
提出一种基于遗传算法的顾客行为特征提取算法。首先,采用Tanimoto 相似度来度量顾客间购买行为,并设计遗传聚类算法对顾客群体进行划分,把具有相似购买行为顾客聚集为一类。然后,针对不同顾客群体的购买行为特征,设计一种基于遗传算法的多种群特征提取方法,从各个子群体中发现顾客的购买行为的知识。为了增强种群内部协同进化能力和规则质量,我们采用最近邻替代遗传策略和局部搜索策略。使用实际零售数据集对整个算法进行验证,并与经典的Apriori算法进行比较。实验结果表明该算法在不需要产生频繁项集的情况下,可较高效生成精简规则集,在规则形式方面也更加灵活。最后,对实验结果进行详细分析。 相似文献
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SPARQL graph pattern rewriting for OWL-DL inference queries 总被引:1,自引:1,他引:0
This paper focuses on the issue of OWL-DL ontology queries implemented in SPARQL. Currently, ontology repositories construct
inference ontology models, and match SPARQL queries to the models, to derive inference results. Because an inference model
uses much more storage space than the original model, and cannot be reused as inference requirements vary, this method is
not suitable for large-scale deployment. To solve this problem, this paper proposes a novel method that passes rewritten SPARQL
queries to the original ontology model, to retrieve inference results. We define OWL-DL inference rules and apply them to
rewriting Graph Patterns in queries. The paper classifies the inference rules and discusses how these rules affect query rewriting.
To illustrate the advantages of our proposal, we present a prototype system based on Jena, and address query optimization,
to eliminate the disadvantages of augmented query sentences. We perform a set of query tests and compare the results with
related works. The results show that the proposed method results in significantly improved query efficiency, without compromising
completeness or soundness.
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Doo-Kwon BaikEmail: |
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随着电子商务的不断发展,用户的分析和分类对电子商务网站来说越来越重要。因此需要一个行之有效的方法来进行用户分类并对其进行个性化服务。在本文中,我们提出了一种可以根据用户的网页访问记录和网上交易记录来动态地对顾客进行分类的方法,主要是利用了改进型的朴素贝叶斯分类器,对用户在网站上的行为进行分类,从而得到用户的分类信息,其结果可以作为提供个性化服务的依据。文章通过实验证明了上述方法的有效性和正确性。 相似文献
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介绍了一种移动计算环境下基于移动Agent的查询请求处理方法一基于区域管理的查询管理模式(ZQTM),并在此基础上提出了在该模式下的查询区域管理方法及移动查询结果的特殊获取方法。 相似文献
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随着电子商务的不断发展,对用户的分析和分类越来越重要,因此需要一个行之有效的方法来对用户进行分类。针对网站日志数据的特点和各种数据挖掘算法的应用特征,尝试用基于关联规则的分类算法来对网站客户进行分类。实验证明此方法是有效的,其结果可以作为提供个性化服务的依据。 相似文献
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Yun Chen Guozheng Zhang Dengfeng Hu Chuan Fu 《Journal of Intelligent Manufacturing》2007,18(4):513-517
Customer Segmentation is an increasingly pressing issue in today’s over-competitive commercial area. More and more literatures
have researched the application of data mining technology in customer segmentation, and achieved sound effectives. But most
of them segment customer only by single data mining technology from a special view, rather than from systematical framework.
Furthermore, one of the key purposes of customer segmentation is customer retention. Although previous segment methods may
identify which group needs more care, it is unable to identify customer churn trend for taking different actions. This paper
focus on proposing a customer segmentation framework based on data mining and constructs a new customer segmentation method
based on survival character. The new customer segmentation method consists of two steps. Firstly, with K-means clustering
arithmetic, customers are clustered into different segments in which customers have the similar survival characters (churn
trend). Secondly, each cluster’s survival/hazard function is predicted by survival analyzing, the validity of clustering is
tested and customer churn trend is identified. The method mentioned above has been applied to a dataset from China Telecom,
which acquired some useful management measures and suggestions. Some propositions for further research is also suggested. 相似文献