The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Modeling score distributions for combining the outputs of search engines
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
The Importance of Prior Probabilities for Entry Page Search
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Simple BM25 extension to multiple weighted fields
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Relevance weighting for query independent evidence
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Multinomial randomness models for retrieval with document fields
ECIR'07 Proceedings of the 29th European conference on IR research
CLEF'05 Proceedings of the 6th international conference on Cross-Language Evalution Forum: accessing Multilingual Information Repositories
Learning to select a ranking function
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
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The application of query-independent features, such as PageRank, can boost the retrieval effectiveness of a Web Information Retrieval (IR) system. In some previous works, a query-independent feature is uniformly applied to all queries. Other works predict the most useful feature based on the query type. However, the accuracy of the current query type prediction methods is not high. In this paper, we investigate a novel approach that applies the most appropriate query-independent feature on a per-query basis, and does not require the knowledge of the query type. The approach is based on an estimate of the divergence between the retrieved document scores' distributions prior to, and after the integration of a query-independent feature. We evaluate our approach on the TREC .GOV Web test collection and the mixed topic sets from TREC 2003 & 2004 Web search tasks. Our experimental results demonstrate that the selective application of a query-independent feature on a per-query basis is very effective and robust. In particular, it outperforms a query type prediction-based method, even when this method is simulated with a 100% query type prediction accuracy.