Approach to deep Web data acquiring based on circular strategy and dynamic knowledge - Xue-feng XIAN; Zhi-ming CUI; Peng-peng ZHAO; Yin-hong LIANG; Li-gang FANG (Tongxin xuebao)
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.