All Outputs (2)

Query performance prediction and effectiveness evaluation without relevance judgments: Two sides of the same coin (2018)
Presentation / Conference Contribution
Mizzaro, S., Mothe, J., Roitero, K., & Ullah, M. Z. (2018, July). Query performance prediction and effectiveness evaluation without relevance judgments: Two sides of the same coin. Presented at SIGIR '18: The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, Ann Arbor, MI, USA

Some methods have been developed for automatic effectiveness evaluation without relevance judgments. We propose to use those methods, and their combination based on a machine learning approach, for query performance prediction. Moreover, since predic... Read More about Query performance prediction and effectiveness evaluation without relevance judgments: Two sides of the same coin.

Query performance prediction focused on summarized letor features (2018)
Presentation / Conference Contribution
Chifu, A., Laporte, L., Mothe, J., & Ullah, M. Z. (2018, July). Query performance prediction focused on summarized letor features. Presented at SIGIR '18: The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, Ann Arbor, MI, USA

Query performance prediction (QPP) aims at automatically estimating the information retrieval system effectiveness for any user's query. Previous work has investigated several types of pre- and post-retrieval query performance predictors; the latter... Read More about Query performance prediction focused on summarized letor features.