A Deep Web Database Sampling Method Based on High Correlation Keywords

Yongqing Zheng, Yufang Bian, Xin Du, Hongchen Wu
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引用次数: 1

Abstract

Evaluation of the Deep Web data sources must be based on the data in the Web databases, then how to select the most representative keywords as a query word to obtain a large number of uniformly distributed data is a major difficulty, this paper proposed a Deep Web database sampling method based on high correlation keyword, using a graph based keyword-connected network to get query words, the method can get a random sample of high-quality data from the Deep Web data source more efficiently.
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一种基于高相关性关键词的深度网络数据库采样方法
评估深层网络数据源中的数据必须基于Web数据库,那么如何选择最具代表性的关键词作为一个查询词获取大量均匀分布的数据是一个主要的困难,提出了一种深层网络数据库基于高度相关关键字的抽样方法,使用一个基于图的keyword-connected网络查询词,该方法可以获得高质量的随机样本的数据更有效地深层网络数据源。
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