Query Performance Prediction: Theory, Techniques and Applications
Query performance prediction (QPP) is a key task in information retrieval (IR), focusing on estimating the retrieval quality of a given query without relying on human-labeled relevance judgments. Over the decades, QPP has gained increasing significance, with a surge in research activity in recent years. It has proven to benefit various aspects of retrieval, such as optimizing retrieval effectiveness by selecting the most appropriate ranking function for each query.
Authors
- Negar Arabzadeh (ORCID: https://orcid.org/0000-0002-4411-7089)
- Mohammad Aliannejadi (ORCID: https://orcid.org/0000-0002-9447-4172)
- Ebrahim Bagheri (ORCID: https://orcid.org/0000-0002-5148-6237)
- Chuan Meng (ORCID: https://orcid.org/0000-0002-1434-7596)
Institutions
- University of Waterloo (CA)
- Toronto Metropolitan University (CA)
- University of Amsterdam (NL)
Publication Details
- Published
- 2025-02-26
- DOI
- https://doi.org/10.1145/3701551.3703480
- Citations
- 3
- Primary Topic
- Data Management and Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 4.46