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Incorporating Explicit Knowledge in Pre-trained Language Models for Passage Re-ranking

Authors:

Shuaiqiang Wang,

Dawei YinAuthors Info & Claims

SIGIR '22: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

Pages 1490 - 1501

https://doi.org/10.1145/3477495.3531997

Published: 07 July 2022 Publication History

Abstract

Passage re-ranking is to obtain a permutation over the candidate passage set from retrieval stage. Re-rankers have been boomed by Pre-trained Language Models (PLMs) due to their overwhelming advantages in natural language understanding. However, existing PLM based re-rankers may easily suffer from vocabulary mismatch and lack of domain specific knowledge. To alleviate these problems, explicit knowledge contained in knowledge graph is carefully introduced in our work. Specifically, we employ the existing knowledge graph which is incomplete and noisy, and first apply it in passage re-ranking task. To leverage a reliable knowledge, we propose a novel knowledge graph distillation method and obtain a knowledge meta graph as the bridge between query and passage. To align both kinds of embedding in the latent space, we employ PLM as text encoder and graph neural network over knowledge meta graph as knowledge encoder. Besides, a novel knowledge injector is designed for the dynamic interaction between text and knowledge encoder. Experimental results demonstrate the effectiveness of our method especially in queries requiring in-depth domain knowledge.

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Index Terms

Incorporating Explicit Knowledge in Pre-trained Language Models for Passage Re-ranking
1. Information systems
  1. Information retrieval
    1. Document representation
      1. Content analysis and feature selection
    2. Retrieval models and ranking

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Published In

cover image ACM Conferences

SIGIR '22: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

July 2022

3569 pages

ISBN:9781450387323

DOI:10.1145/3477495

General Chairs:
Enrique Amigo
UNED
,
Pablo Castells
UAM and Amazon
,
Julio Gonzalo
UNED
,
Program Chairs:
Ben Carterette
Spotify
,
J. Shane Culpepper
RMIT University
,
Gabriella Kazai
Waseda University

Copyright © 2022 Owner/Author.

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike International 4.0 License.

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Published: 07 July 2022

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SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

July 11 - 15, 2022

Madrid, Spain

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Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Cited By

Chong LMa DChen YLv X(2025)Reusing Keywords for Fine-grained Representations and MatchingsDatabase Systems for Advanced Applications10.1007/978-981-97-5779-4_6(83-98)Online publication date: 11-Jan-2025
https://doi.org/10.1007/978-981-97-5779-4_6
Xia LShen WFan WWang G(2024)Knowledge-Aware Learning Framework Based on Schema Theory to Complement Large Learning ModelsJournal of Management Information Systems10.1080/07421222.2024.234082741:2(453-486)Online publication date: 24-Jun-2024
https://doi.org/10.1080/07421222.2024.2340827
Gao WZheng CZhu XDeng HWang YHu G(2024)Knowledge-injected prompt learning for actionable information extraction from crisis-related tweetsComputers and Electrical Engineering10.1016/j.compeleceng.2024.109398118(109398)Online publication date: Sep-2024
https://doi.org/10.1016/j.compeleceng.2024.109398
Hu LLiu ZZhao ZHou LNie LLi J(2023)A Survey of Knowledge Enhanced Pre-Trained Language ModelsIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2023.331000236:4(1413-1430)Online publication date: 30-Aug-2023
https://dl.acm.org/doi/10.1109/TKDE.2023.3310002
Xiao XDai HDong QNiu SLiu YLiu P(2023)Incorporating Social-Aware User Preference for Video RecommendationWeb Information Systems Engineering – WISE 202310.1007/978-981-99-7254-8_42(544-558)Online publication date: 25-Oct-2023
https://dl.acm.org/doi/10.1007/978-981-99-7254-8_42
Nagumothu DOfoghi BEklund P(2023)Semantic Triple-Assisted Learning for Question Answering Passage Re-rankingDocument Analysis and Recognition - ICDAR 202310.1007/978-3-031-41682-8_16(249-264)Online publication date: 21-Aug-2023
https://dl.acm.org/doi/10.1007/978-3-031-41682-8_16

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