Efficient query evaluation using a two-level retrieval process
Efficient query evaluation using a two-level retrieval process
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DOI：
10.1145/956863.956944
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发表时间：
2003-11
期刊：
影响因子：
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通讯作者：
A. Broder;David Carmel;Michael Herscovici;A. Soffer;Jason Y. Zien
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文献类型：
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作者：
A. Broder;David Carmel;Michael Herscovici;A. Soffer;Jason Y. Zien
我们提出了一种基于两级方法的高效查询评估方法：在第一级，我们的方法并行迭代查询术语发布，并使用近似评估来识别候选文档，仅考虑术语出现的部分信息，并且不考虑查询独立因素；在第二级，对有前途的候选人进行全面评估并计算他们的确切分数。使用动态修剪技术可以显着提高评估过程的效率，而效率成本却非常低。用户可以根据分配给查询评估的时间来控制修剪量。通过实验，使用 TREC Web Track 数据，我们确定我们的算法将完整评估的总数显着减少了 90% 以上，几乎没有任何精度或召回率损失。我们方法的核心是有效实现一种新的布尔结构，称为 WAND 或弱 AND，它可能具有独立的意义。
We present an efficient query evaluation method based on a two level approach: at the first level, our method iterates in parallel over query term postings and identifies candidate documents using an approximate evaluation taking into account only partial information on term occurrences and no query independent factors; at the second level, promising candidates are fully evaluated and their exact scores are computed. The efficiency of the evaluation process can be improved significantly using dynamic pruning techniques with very little cost in effectiveness. The amount of pruning can be controlled by the user as a function of time allocated for query evaluation. Experimentally, using the TREC Web Track data, we have determined that our algorithm significantly reduces the total number of full evaluations by more than 90%, almost without any loss in precision or recall. At the heart of our approach there is an efficient implementation of a new Boolean construct called WAND or Weak AND that might be of independent interest.