针对网页质量参差不齐、重要程度差别巨大的问题，提出了按照网页重要程度确定其剪枝幅度的静态索引剪枝方法，并在GOV2 数据集上进行了验证． 实验结果表明:这种方法体现了静态索引剪枝能极大降低存储需求、提高查询效率的优点; 当剪枝后的索引大小是原始大小的13%时，P@ 10、P@ 20  值能达到甚至超过使用完整索引时的结果;在相同的剪枝幅度下，P@ 10、P@ 20 和MAP 都明显好于以往的剪枝方法．

As the quality and importance of Web pages are both variable,paper proposes a static index pruning method which uses the web page importance to determine the ratio of information kept for each document. The result of experiments on GOV2 dataset show that ( 1) the proposed method greatly reduces the storage size and speeds up the search; ( 2) when the pruned index takes only 13% of the original size,P@ 10 and P@ 20 reach or exceed the baseline using full index; and ( 3) by using the proposed method,P@ 10,P@ 20  and MAP are all better than those of the traditional method at the same pruning level.