Using document-quality measures to predict web-search effectiveness

Abstract

The query-performance prediction task is estimating retrieval effectiveness in the absence of relevance judgments. The task becomes highly challenging over theWeb due to, among other reasons, the effect of low quality (e.g., spam) documents on retrieval performance. To address this challenge, we present a novel prediction approach that utilizes queryindependent document-quality measures. While using these measures was shown to improve Web-retrieval effectiveness, this is the first study demonstrating the clear merits of using them for query-performance prediction. Evaluation performed with large scale Web collections shows that our methods post prediction quality that often surpasses that of state-of-the-art predictors, including those devised specifically for Web retrieval. © 2013 Springer-Verlag.