An evolutionary approach to query-sampling for heterogeneous systems
An evolutionary approach to query-sampling for heterogeneous systems
复制标题
异构系统查询采样的进化方法
DOI：
10.1016/j.eswa.2009.05.013
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
Jason J. Jung
中科院分区：
文献类型：
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作者：
Jason J. Jung
在分布式环境中，关于信息源的资源描述（例如，数据库和储存库）对于确定应当顺序地向哪个信息源发送查询是非常重要的。这项工作的目标是找出语义之间的关系，有效地集成资源描述的来源。因此，在本文中，我们提出了一种进化的方法，以最大限度地提高歧视的来源之间的性能。我们结合联合收割机的查询抽样方法和进化方法。这两种方法分别用于资源描述的提取和描述的优化集成。为了评估所提出的查询抽样方法的性能，我们建立了53个信息源。我们将所提出的方法推荐的排名列表与用户反馈进行了比较（即，理想等级），并且还计算了源之间所发现的语义关系的精确度和查全率。
In distributed environment, resource descriptions about information sources (e.g., databases and repositories) are significantly important to determine which information source queries should be sequentially sent to. The goal of this work is to find out semantic relationships between the sources for efficiently integrating the resource descriptions. Thereby, in this paper, we propose an evolutionary approach to maximize the discrimination performance among the sources. We combine a query-sampling method and evolutionary method. These two methods are used for extracting the resource descriptions, and optimally integrating the descriptions, respectively. For evaluating the performance of the proposed query-sampling method, we have set up 53 information sources. We have compared the ranking lists recommended by the proposed method with user feedbacks (i.e., ideal ranks), and also computed the precision and recall of discovered semantic relationships between the sources.