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用进化算法随时查询并回答RDF相关问题

Anytime Query Answering in RDF through Evolutionary Algorithms
课程网址: http://videolectures.net/iswc08_oren_aqa/  
主讲教师: Eyal Oren
开课单位: 阿姆斯特丹自由大学
开课时间: 2008-11-24
课程语种: 英语
中文简介:
我们提出了一种通过进化搜索算法来回答RDF数据查询的技术,使用指纹和Bloom过滤器来快速近似地评估生成的解决方案。与传统的数据库方法相比,我们的进化方法有几个优点风格查询回答。首先,结果质量单调增加,并且随着每次演化而收敛,在计算时间和查询结果之间提供任意权衡的“随时”行为;此外,可以通过改变布鲁姆滤波器的大小来调整近似水平。其次,通过Bloom filter压缩,可以在主存中拟合较大的图形,减少了查询求值时对磁盘I/O的需求。最后,由于个体是独立进化的,所以并行执行非常简单。我们提供的原型可以在任意RDF图上评估基本的SPARQL查询,并在大型数据集上显示初始结果。
课程简介: We present a technique for answering queries over RDF data through an evolutionary search algorithm, using fingerprinting and Bloom filters for rapid approximate evaluation of generated solutions. Our evolutionary approach has several advantages compared to traditional database- style query answering. First, the result quality increases monotonically and converges with each evolution, offering “anytime” behaviour with arbitrary trade-off between computation time and query results; in addition, the level of approximation can be tuned by varying the size of the Bloom filters. Secondly, through Bloom filter compression we can fit large graphs in main memory, reducing the need for disk I/O during query evaluation. Finally, since the individuals evolve independently, parallel execution is straightforward. We present our prototype that evaluates basic SPARQL queries over arbitrary RDF graphs and show initial results over large datasets.
关 键 词: 进化搜索算法; RDF数据; Bloom过滤器; 评估解决方案; 数据库; 质量提升
课程来源: 视频讲座网
最后编审: 2019-06-28:chenxin
阅读次数: 24