Neural Disentanglement of Query Difficulty and Semantics-Reference-Cited by-同舟云学术

Neural Disentanglement of Query Difficulty and Semantics

Published:2023-10-21 Issue: Volume: Page:
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Container-title:Proceedings of the 32nd ACM International Conference on Information and Knowledge Management
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Author:

Salamat Sara¹^ORCID,Arabzadeh Negar²^ORCID,Seyedsalehi Shirin¹^ORCID,Bigdeli Amin¹^ORCID,Zihayat Morteza¹^ORCID,Bagheri Ebrahim¹^ORCID

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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