TY - GEN
T1 - Estimating query representativeness for query-performance prediction
AU - Sondak, Mor
AU - Shtok, Anna
AU - Kurland, Oren
PY - 2013
Y1 - 2013
N2 - The query-performance prediction (QPP) task is estimating retrieval effectiveness with no relevance judgments. We present a novel probabilistic framework for QPP that gives rise to an important aspect that was not addressed in previous work; namely, the extent to which the query effectively represents the information need for retrieval. Accordingly, we devise a few query-representativeness measures that utilize relevance language models. Experiments show that integrating the most effective measures with state-of-the-art predictors in our framework often yields prediction quality that significantly transcends that of using the predictors alone.
AB - The query-performance prediction (QPP) task is estimating retrieval effectiveness with no relevance judgments. We present a novel probabilistic framework for QPP that gives rise to an important aspect that was not addressed in previous work; namely, the extent to which the query effectively represents the information need for retrieval. Accordingly, we devise a few query-representativeness measures that utilize relevance language models. Experiments show that integrating the most effective measures with state-of-the-art predictors in our framework often yields prediction quality that significantly transcends that of using the predictors alone.
KW - Query-performance prediction
UR - http://www.scopus.com/inward/record.url?scp=84883107172&partnerID=8YFLogxK
U2 - 10.1145/2484028.2484107
DO - 10.1145/2484028.2484107
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AN - SCOPUS:84883107172
SN - 9781450320344
T3 - SIGIR 2013 - Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval
SP - 853
EP - 856
BT - SIGIR 2013 - Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval
T2 - 36th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2013
Y2 - 28 July 2013 through 1 August 2013
ER -