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Communication Dans Un Congrès Année : 2018

Query Performance Prediction and Effectiveness Evaluation Without Relevance Judgments: Two Sides of the Same Coin

Résumé

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 predicting average precision as it is usually done in query performance prediction literature is sensitive to the reference system that is chosen, we focus on predicting the average of average precision values over several systems. Results of an extensive experimental evaluation on ten TREC collections show that our proposed methods outperform state-of-the-art query performance predictors.
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Dates et versions

hal-03623111 , version 1 (29-03-2022)

Identifiants

  • HAL Id : hal-03623111 , version 1
  • OATAO : 22399

Citer

Stefano Mizzaro, Josiane Mothe, Kevin Roitero, Md Zia Ullah. Query Performance Prediction and Effectiveness Evaluation Without Relevance Judgments: Two Sides of the Same Coin. 41st International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2018), Jul 2018, Ann-Arbor, MI, United States. pp.1233-1236. ⟨hal-03623111⟩
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