Selectivity Estimation Based on 7ipf Distribution and Attribute Correlation
基于Zipf分布与属性相关性的选择性估计

In Deep Web data integration,some Web database interfaces express exclusive predicates,which permit only one predicate to be selected. Accurately and efficiently estimating the selectivity of each exclusive query is of critical importance to optimal query translation. In this paper, we proposed a novel selectivity estimation method. Firstly, we computed the Attribute Correlation and access approximately random attributclevel sample through submitting the query on the least correlative attribute to the real Web database. hhen we computed Zipf equation aided by the information of word rank from the sample and the actual selectivity of several words from the real Web database. Finally, the selectivity of any word on the infinitcvaluc attribute was derived by the Zipf equation. An experimental evaluation of the proposed selectivity estimation method was provided and experimental results are highly accurate.