research-article

On Type-Aware Entity Retrieval

Authors:

Darío Garigliotti,

Krisztian BalogAuthors Info & Claims

ICTIR '17: Proceedings of the ACM SIGIR International Conference on Theory of Information Retrieval

Pages 27 - 34

https://doi.org/10.1145/3121050.3121054

Published: 01 October 2017 Publication History

Abstract

Today, the practice of returning entities from a knowledge base in response to search queries has become widespread. One of the distinctive characteristics of entities is that they are typed, i.e., assigned to some hierarchically organized type system (type taxonomy). The primary objective of this paper is to gain a better understanding of how entity type information can be utilized in entity retrieval. We perform this investigation in an idealized "oracle" setting, assuming that we know the distribution of target types of the relevant entities for a given query. We perform a thorough analysis of three main aspects: (i) the choice of type taxonomy, (ii) the representation of hierarchical type information, and (iii) the combination of type-based and term-based similarity in the retrieval model. Using a standard entity search test collection based on DBpedia, we find that type information proves most useful when using large type taxonomies that provide very specific types. We provide further insights on the extensional coverage of entities and on the utility of target types.

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Cited By

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
Garigliotti D(2021)Task-based support in search enginesACM SIGIR Forum10.1145/3451964.345198054:1(1-2)Online publication date: 19-Feb-2021
https://dl.acm.org/doi/10.1145/3451964.3451980
Chatterjee SDietz LDiaz FShah CSuel TCastells PJones RSakai T(2021)Entity Retrieval Using Fine-Grained Entity AspectsProceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3404835.3463035(1662-1666)Online publication date: 11-Jul-2021
https://dl.acm.org/doi/10.1145/3404835.3463035
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Index Terms

On Type-Aware Entity Retrieval
1. Information systems
  1. Information retrieval
    1. Retrieval models and ranking

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cover image ACM Conferences

ICTIR '17: Proceedings of the ACM SIGIR International Conference on Theory of Information Retrieval

October 2017

348 pages

ISBN:9781450344906

DOI:10.1145/3121050

General Chairs:
Jaap Kamps
University of Amsterdam, The Netherlands
,
Evangelos Kanoulas
University of Amsterdam, The Netherlands
,
Maarten de Rijke
University of Amsterdam, The Netherlands
,
Program Chairs:
Hui Fang
University of Delaware, USA
,
Emine Yilmaz
University College London, UK

Copyright © 2017 ACM.

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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SIGIR: ACM Special Interest Group on Information Retrieval

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Association for Computing Machinery

New York, NY, United States

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Published: 01 October 2017

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ICTIR '17: ACM SIGIR International Conference on the Theory of Information Retrieval

October 1 - 4, 2017

Amsterdam, The Netherlands

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ICTIR '17 Paper Acceptance Rate 27 of 54 submissions, 50%;

Overall Acceptance Rate 235 of 527 submissions, 45%

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Cited By

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
Garigliotti D(2021)Task-based support in search enginesACM SIGIR Forum10.1145/3451964.345198054:1(1-2)Online publication date: 19-Feb-2021
https://dl.acm.org/doi/10.1145/3451964.3451980
Chatterjee SDietz LDiaz FShah CSuel TCastells PJones RSakai T(2021)Entity Retrieval Using Fine-Grained Entity AspectsProceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3404835.3463035(1662-1666)Online publication date: 11-Jul-2021
https://dl.acm.org/doi/10.1145/3404835.3463035
Lv S(2021)Improving Discriminative Entity Retriever with Generative Tasks2021 2nd International Conference on Electronics, Communications and Information Technology (CECIT)10.1109/CECIT53797.2021.00120(656-660)Online publication date: Dec-2021
https://doi.org/10.1109/CECIT53797.2021.00120
Nie WWang YSong DLi W(2020)3D Model Retrieval Based on a 3D Shape Knowledge GraphIEEE Access10.1109/ACCESS.2020.30135958(142632-142641)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3013595
Garigliotti DAlbakour DMartinez MBalog KFang YZhang YAllan JBalog KCarterette BGuo J(2019)Unsupervised Context Retrieval for Long-tail EntitiesProceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval10.1145/3341981.3344244(225-228)Online publication date: 26-Sep-2019
https://dl.acm.org/doi/10.1145/3341981.3344244
Dietz LPiwowarski BChevalier MGaussier EMaarek YNie JScholer F(2019)ENT RankProceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3331184.3331257(215-224)Online publication date: 18-Jul-2019
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Lin XLam WLai KSong DLiu TSun LBruza PMelucci MSebastiani FYang G(2018)Entity Retrieval in the Knowledge Graph with Hierarchical Entity Type and ContentProceedings of the 2018 ACM SIGIR International Conference on Theory of Information Retrieval10.1145/3234944.3234963(211-214)Online publication date: 10-Sep-2018
https://dl.acm.org/doi/10.1145/3234944.3234963
Dietz LKotov AMeij ECollins-Thompson KMei QDavison BLiu YYilmaz E(2018)Utilizing Knowledge Graphs for Text-Centric Information RetrievalThe 41st International ACM SIGIR Conference on Research & Development in Information Retrieval10.1145/3209978.3210187(1387-1390)Online publication date: 27-Jun-2018
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Shen JXiao JHe XShang JSinha SHan JCollins-Thompson KMei QDavison BLiu YYilmaz E(2018)Entity Set Search of Scientific LiteratureThe 41st International ACM SIGIR Conference on Research & Development in Information Retrieval10.1145/3209978.3210055(565-574)Online publication date: 27-Jun-2018
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