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ENT Rank: Retrieving Entities for Topical Information Needs through Entity-Neighbor-Text Relations

Author:

Laura DietzAuthors Info & Claims

SIGIR'19: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval

Pages 215 - 224

https://doi.org/10.1145/3331184.3331257

Published: 18 July 2019 Publication History

Abstract

Related work has demonstrated the helpfulness of utilizing information about entities in text retrieval; here we explore the converse: Utilizing information about text in entity retrieval. We model the relevance of Entity-Neighbor-Text (ENT) relations to derive a learning-to-rank-entities model.

We focus on the task of retrieving (multiple) relevant entities in response to a topical information need such as "Zika fever". The ENT Rank model is designed to exploit semi-structured knowledge resources such as Wikipedia for entity retrieval. The ENT Rank model combines (1) established features of entity-relevance, with (2) information from neighboring entities (co-mentioned or mentioned-on-page) through (3) relevance scores of textual contexts through traditional retrieval models such as BM25 and RM3.

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Cited By

Jafarzadeh PEnsan FAli Akbar Alavi MZarrinkalam F(2025)A Knowledge Graph Embedding Model for Answering Factoid Entity QuestionsACM Transactions on Information Systems10.1145/367800343:2(1-27)Online publication date: 24-Jan-2025
https://dl.acm.org/doi/10.1145/3678003
Jafarzadeh PAmirmahani ZEnsan F(2024)Learning contextual representations for entity retrievalApplied Intelligence10.1007/s10489-024-05430-054:19(8820-8840)Online publication date: 4-Jul-2024
https://doi.org/10.1007/s10489-024-05430-0
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
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Index Terms

ENT Rank: Retrieving Entities for Topical Information Needs through Entity-Neighbor-Text Relations
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
2. Information systems
  1. Information retrieval
    1. Retrieval models and ranking

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Published In

cover image ACM Conferences

SIGIR'19: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval

July 2019

1512 pages

ISBN:9781450361729

DOI:10.1145/3331184

General Chairs:
Benjamin Piwowarski
CNRS - Sorbonne Universite, France
,
Max Chevalier
Universite de Toulouse, CNRS, France
,
Eric Gaussier
Universite Grenoble Alpes, CNRS, France
,
Program Chairs:
Yoelle Maarek
Amazon Research, Israel
,
Jian-Yun Nie
University of Montreal, Canada
,
Falk Scholer
RMIT University, Australia

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SIGIR: ACM Special Interest Group on Information Retrieval

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Published: 18 July 2019

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National Science Foundation

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SIGIR '19

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SIGIR

SIGIR '19: The 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval

July 21 - 25, 2019

Paris, France

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SIGIR'19 Paper Acceptance Rate 84 of 426 submissions, 20%;

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

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Cited By

Jafarzadeh PEnsan FAli Akbar Alavi MZarrinkalam F(2025)A Knowledge Graph Embedding Model for Answering Factoid Entity QuestionsACM Transactions on Information Systems10.1145/367800343:2(1-27)Online publication date: 24-Jan-2025
https://dl.acm.org/doi/10.1145/3678003
Jafarzadeh PAmirmahani ZEnsan F(2024)Learning contextual representations for entity retrievalApplied Intelligence10.1007/s10489-024-05430-054:19(8820-8840)Online publication date: 4-Jul-2024
https://doi.org/10.1007/s10489-024-05430-0
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
Guo MZhou ZGotz DWang Y(2023)GRAFS: Graphical Faceted Search System to Support Conceptual Understanding in Exploratory SearchACM Transactions on Interactive Intelligent Systems10.1145/358831913:2(1-36)Online publication date: 31-Mar-2023
https://dl.acm.org/doi/10.1145/3588319
Keyhanipour A(2023)Graph-based comparative analysis of learning to rank datasetsInternational Journal of Data Science and Analytics10.1007/s41060-023-00406-8Online publication date: 30-Jun-2023
https://doi.org/10.1007/s41060-023-00406-8
Oza PDietz L(2023)Entity Embeddings for Entity Ranking: A Replicability StudyAdvances in Information Retrieval10.1007/978-3-031-28241-6_8(117-131)Online publication date: 2-Apr-2023
https://dl.acm.org/doi/10.1007/978-3-031-28241-6_8
Oza PAl Hasan MXiong L(2022)Identify Relevant Entities Through Text UnderstandingProceedings of the 31st ACM International Conference on Information & Knowledge Management10.1145/3511808.3557819(5124-5127)Online publication date: 17-Oct-2022
https://dl.acm.org/doi/10.1145/3511808.3557819
Kasturia VGohsen MHagen MSelcuk Candan KLiu HAkoglu LLuna Dong XTang J(2022)Query Interpretations from Entity-Linked SegmentationsProceedings of the Fifteenth ACM International Conference on Web Search and Data Mining10.1145/3488560.3498532(449-457)Online publication date: 11-Feb-2022
https://dl.acm.org/doi/10.1145/3488560.3498532
Mai CQiu MLuo KPeng ZLiu JYuan CHuang YSelcuk Candan KLiu HAkoglu LLuna Dong XTang J(2022)Pretraining Multi-modal Representations for Chinese NER Task with Cross-Modality AttentionProceedings of the Fifteenth ACM International Conference on Web Search and Data Mining10.1145/3488560.3498450(726-734)Online publication date: 11-Feb-2022
https://dl.acm.org/doi/10.1145/3488560.3498450
Gerritse EHasibi Fde Vries AAmigo ECastells PGonzalo JCarterette BCulpepper JKazai G(2022)Entity-aware Transformers for Entity SearchProceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3477495.3531971(1455-1465)Online publication date: 6-Jul-2022
https://dl.acm.org/doi/10.1145/3477495.3531971
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