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JointSem: Combining Query Entity Linking and Entity based Document Ranking

Authors:

Chenyan Xiong,

Zhengzhong Liu,

Jamie Callan,

Eduard HovyAuthors Info & Claims

CIKM '17: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management

Pages 2391 - 2394

https://doi.org/10.1145/3132847.3133048

Published: 06 November 2017 Publication History

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Abstract

Entity-based ranking systems often employ entity linking systems to align entities to query and documents. Previously, entity linking systems were not designed specifically for search engines and were mostly used as a preprocessing step. This work presents JointSem, a joint semantic ranking system that combines query entity linking and entity-based document ranking. In JointSem, the spotting and linking signals are used to describe the importance of candidate entities in the query, and the linked entities are utilized to provide additional ranking features for the documents. The linking signals and the ranking signals are combined by a joint learning-to-rank model, and the whole system is fully optimized towards end-to-end ranking performance. Experiments on TREC Web Track datasets demonstrate the effectiveness of joint learning of entity linking and entity-based ranking.

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Cited By

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Chatterjee SMackie IDalton J(2024)DREQ: Document Re-ranking Using Entity-Based Query UnderstandingAdvances in Information Retrieval10.1007/978-3-031-56027-9_13(210-229)Online publication date: 24-Mar-2024
https://dl.acm.org/doi/10.1007/978-3-031-56027-9_13
Dietz LBast HChatterjee SDalton JNie JNogueira RChen HDuh WHuang HKato MMothe JPoblete B(2023)Neuro-Symbolic Representations for Information RetrievalProceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3539618.3594246(3436-3439)Online publication date: 19-Jul-2023
https://dl.acm.org/doi/10.1145/3539618.3594246
Li XTian BTian X(2023)Scientific Documents Retrieval Based on Graph Convolutional Network and Hesitant Fuzzy SetIEEE Access10.1109/ACCESS.2023.325923411(27942-27954)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3259234
Show More Cited By

Index Terms

JointSem: Combining Query Entity Linking and Entity based Document Ranking
1. Information systems
  1. Data management systems
    1. Information integration
      1. Entity resolution
  2. Information retrieval
    1. Information retrieval query processing
      1. Query representation
    2. Retrieval models and ranking

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Information & Contributors

Information

Published In

CIKM '17: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management

November 2017

2604 pages

ISBN:9781450349185

DOI:10.1145/3132847

General Chairs:
Ee-Peng Lim
Singapore Management University, Singapore
,
Marianne Winslett
University of Illinois at Urbana-Champaign, USA, and Advanced Digital Sciences Center, Singapore
,
Program Chairs:
Mark Sanderson
RMIT, Australia
,
Ada Fu
Chinese University of Hong Kong, Hong Kong
,
Jimeng Sun
Georgia Tech, USA
,
Shane Culpepper
RMIT, Australia
,
Eric Lo
Chinese University of Hong Kong, Hong Kong
,
Joyce Ho
Emory University, USA
,
Debora Donato
Mix Tech, Inc., USA
,
Rakesh Agrawal
Data Insights Laboratories, USA
,
Yu Zheng
Microsoft Research Asia, China
,
Carlos Castillo
Qatar Computing Research Institute, Qatar
,
Aixin Sun
Nanyang Technological University, Singapore
,
Vincent S. Tseng
National Cheng Kung University, Taiwan
,
Chenliang Li
Wuhan University, China

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 November 2017

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Short-paper

Funding Sources

National Science Foundation
Allen Institute for Artificial Intelligence

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CIKM '17

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CIKM '17: ACM Conference on Information and Knowledge Management

November 6 - 10, 2017

Singapore, Singapore

Acceptance Rates

CIKM '17 Paper Acceptance Rate 171 of 855 submissions, 20%;

Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

Upcoming Conference

CIKM '25

Sponsor:
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The 34th ACM International Conference on Information and Knowledge Management

November 10 - 14, 2025

Seoul , Republic of Korea

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Cited By

View all

Chatterjee SMackie IDalton J(2024)DREQ: Document Re-ranking Using Entity-Based Query UnderstandingAdvances in Information Retrieval10.1007/978-3-031-56027-9_13(210-229)Online publication date: 24-Mar-2024
https://dl.acm.org/doi/10.1007/978-3-031-56027-9_13
Dietz LBast HChatterjee SDalton JNie JNogueira RChen HDuh WHuang HKato MMothe JPoblete B(2023)Neuro-Symbolic Representations for Information RetrievalProceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3539618.3594246(3436-3439)Online publication date: 19-Jul-2023
https://dl.acm.org/doi/10.1145/3539618.3594246
Li XTian BTian X(2023)Scientific Documents Retrieval Based on Graph Convolutional Network and Hesitant Fuzzy SetIEEE Access10.1109/ACCESS.2023.325923411(27942-27954)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3259234
Dietz LBast HChatterjee SDalton JMeij Ede Vries A(2023)ECIR 23 Tutorial: Neuro-Symbolic Approaches for Information RetrievalAdvances in Information Retrieval10.1007/978-3-031-28241-6_33(324-330)Online publication date: 2-Apr-2023
https://dl.acm.org/doi/10.1007/978-3-031-28241-6_33
Abdollahi S(2022)User Access Models to Event-Centric InformationCompanion Proceedings of the Web Conference 202210.1145/3487553.3524193(329-333)Online publication date: 25-Apr-2022
https://dl.acm.org/doi/10.1145/3487553.3524193
Qi YXin JLi N(2022)An Expansion-based Document Ranking Framework Incorporated with Core Concern Capturing2022 5th International Conference on Intelligent Autonomous Systems (ICoIAS)10.1109/ICoIAS56028.2022.9931242(370-375)Online publication date: 23-Sep-2022
https://doi.org/10.1109/ICoIAS56028.2022.9931242
Shanaz ARagel R(2021)Wikidata based Person Entity Linking in News Articles2021 10th International Conference on Information and Automation for Sustainability (ICIAfS)10.1109/ICIAfS52090.2021.9606139(66-70)Online publication date: 11-Aug-2021
https://doi.org/10.1109/ICIAfS52090.2021.9606139
Hosseini HBagheri E(2021)Learning to rank implicit entities on TwitterInformation Processing & Management10.1016/j.ipm.2021.10250358:3(102503)Online publication date: May-2021
https://doi.org/10.1016/j.ipm.2021.102503
Devezas JNunes S(2021)A Review of Graph-Based Models for Entity-Oriented SearchSN Computer Science10.1007/s42979-021-00828-w2:6Online publication date: 30-Aug-2021
https://doi.org/10.1007/s42979-021-00828-w
Li ZXu GLiang XLi FWang LZhang D(2019)Exploring the Importance of Entities in Semantic RankingInformation10.3390/info1002003910:2(39)Online publication date: 24-Jan-2019
https://doi.org/10.3390/info10020039
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Word-Entity Duet Representations for Document Ranking

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