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中文摘要：
针对目前deep Web数据集成在数据获取方面存在代价大和查询选择效率低等问题，提出了一种基于循环策略和动态知识的deep Web数据获取方法，该方法根据同领域数据源之间的关联关系，提出使用循环策略分多次完成数据源的数据获取，同时利用集成系统已获取的数据动态构建知识，并设计了基于集成系统动态知识的查询选择方法。与现有方法比较该方法能降低数据获取的代价，提高查询选择的准确性。实验结果表明，该方法有效地提高了deep Web数据集成的数据获取效率。
英文摘要：
Concerning on the acquisition problems on deep Web data integration such as high cost and low efficiency of query selecting, a novel deep Web data acquiring method was proposed based on circular strategy and dynamic knowledge. According to the relationship between deep Web data sources from the same domain, the circulation strategic acquisition of data source in batches was applied in such method, as well as a designed method of query selecting on dynamic knowledge based on integrated systematic. Compared with current, the method reduces the acquisition cost and with more accuracy. Experimental results show that the method can raise the acquisition efficiency of deep Web data integration.
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