Neural Disentanglement of Query Difficulty and Semantics
Author:
Affiliation:
1. Toronto Metropolitan University, Toronto, ON, Canada
2. University of Waterloo, Waterloo, ON, Canada
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3583780.3615189
Reference46 articles.
1. Matches Made in Heaven: Toolkit and Large-Scale Datasets for Supervised Query Reformulation
2. Query Performance Prediction Through Retrieval Coherency
3. Negar Arabzadeh , Maryam Khodabakhsh , and Ebrahim Bagheri . 2021 . BERTQPP: contextualized pre-trained transformers for query performance prediction . In Proceedings of the 30th ACM Int'l Conference on Information & Knowledge Management. 2857--2861 . Negar Arabzadeh, Maryam Khodabakhsh, and Ebrahim Bagheri. 2021. BERTQPP: contextualized pre-trained transformers for query performance prediction. In Proceedings of the 30th ACM Int'l Conference on Information & Knowledge Management. 2857--2861.
4. Shallow pooling for sparse labels
5. Predicting Efficiency/Effectiveness Trade-offs for Dense vs. Sparse Retrieval Strategy Selection
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