Towards Query Performance Prediction for Neural Information Retrieval: Challenges and Opportunities

Author:

Faggioli Guglielmo1ORCID,Formal Thibault2ORCID,Lupart Simon2ORCID,Marchesin Stefano1ORCID,Clinchant Stephane2ORCID,Ferro Nicola1ORCID,Piwowarski Benjamin3ORCID

Affiliation:

1. University of Padova, Padova, Italy

2. Naver Labs Europe, Meylan, France

3. CNRS / ISIR, Sorbonne Université, Paris, France

Publisher

ACM

Reference114 articles.

1. BERT-QPP: Contextualized Pre-trained transformers for Query Performance Prediction

2. Unsupervised Question Clarity Prediction through Retrieved Item Coherency

3. Neural embedding-based specificity metrics for pre-retrieval query performance prediction

4. Negar Arabzadeh , Fattane Zarrinkalam , Jelena Jovanovic , and Ebrahim Bagheri . 2020 b. Neural Embedding-Based Metrics for Pre-retrieval Query Performance Prediction. In Advances in Information Retrieval - 42nd European Conference on IR Research , ECIR 2020, Lisbon, Portugal, April 14--17, 2020, Proceedings, Part II (Lecture Notes in Computer Science , Vol. 12036), Joemon M. Jose, Emine Yilmaz, Jo a o Magalh a es, Pablo Castells, Nicola Ferro, Má rio J. Silva, and Flá vio Martins (Eds.). Springer, 78-- 85 . https://doi.org/10.1007/978--3-030--45442--5_10 10.1007/978--3-030--45442--5_10 Negar Arabzadeh, Fattane Zarrinkalam, Jelena Jovanovic, and Ebrahim Bagheri. 2020b. Neural Embedding-Based Metrics for Pre-retrieval Query Performance Prediction. In Advances in Information Retrieval - 42nd European Conference on IR Research, ECIR 2020, Lisbon, Portugal, April 14--17, 2020, Proceedings, Part II (Lecture Notes in Computer Science, Vol. 12036), Joemon M. Jose, Emine Yilmaz, Jo a o Magalh a es, Pablo Castells, Nicola Ferro, Má rio J. Silva, and Flá vio Martins (Eds.). Springer, 78--85. https://doi.org/10.1007/978--3-030--45442--5_10

5. Yang Bai Xiaoguang Li Gang Wang Chaoliang Zhang Lifeng Shang Jun Xu Zhaowei Wang Fangshan Wang and Qun Liu. 2020. SparTerm: Learning Term-based Sparse Representation for Fast Text Retrieval. https://doi.org/10.48550/ARXIV.2010.00768 10.48550/ARXIV.2010.00768

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Leveraging LLMs for Unsupervised Dense Retriever Ranking;Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval;2024-07-10

2. Embark on DenseQuest: A System for Selecting the Best Dense Retriever for a Custom Collection;Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval;2024-07-10

3. Query Performance Prediction: From Fundamentals to Advanced Techniques;Lecture Notes in Computer Science;2024

4. BertPE: A BERT-Based Pre-retrieval Estimator for Query Performance Prediction;Lecture Notes in Computer Science;2024

5. Sentiment Difficulty in Aspect-Based Sentiment Analysis;Mathematics;2023-11-14

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3