research-article

A ranking framework for entity oriented search using Markov random fields

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Oren KurlandAuthors Info & Claims

JIWES '12: Proceedings of the 1st Joint International Workshop on Entity-Oriented and Semantic Search

Article No.: 1, Pages 1 - 6

https://doi.org/10.1145/2379307.2379308

Published: 12 August 2012 Publication History

Abstract

In this work we present a general model for entity ranking that is based on the Markov Random Field approach for modeling various types of dependencies between the query and the entity. We show that this model actually extends existing approaches for entity ranking while aggregating all pieces of relevance evidences in a unified way. We evaluated the performance of our model using the INEX datasets. Our results show that our ranking model significantly out-performs leading INEX systems in the tracks of 2007 and 2008, and is equivalent to the best results achieved in the 2009 track.

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Cited By

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
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: 16-Mar-2023
https://doi.org/10.1007/978-3-031-28241-6_8
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cover image ACM Other conferences

JIWES '12: Proceedings of the 1st Joint International Workshop on Entity-Oriented and Semantic Search

August 2012

43 pages

ISBN:9781450316019

DOI:10.1145/2379307

Copyright © 2012 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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Association for Computing Machinery

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Publication History

Published: 12 August 2012

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Israel Science Foundation

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JIWES '12

JIWES '12: 1st Joint International Workshop on Entity-oriented and Semantic Search

August 12, 2012

Oregon, Portland, USA

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Cited By

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
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: 16-Mar-2023
https://doi.org/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
Chatterjee SDietz LAmigo ECastells PGonzalo JCarterette BCulpepper JKazai G(2022)BERT-ERProceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3477495.3531944(1466-1477)Online publication date: 6-Jul-2022
https://dl.acm.org/doi/10.1145/3477495.3531944
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
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
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
https://dl.acm.org/doi/10.1145/3331184.3331257
Kuzi SZhai C(2019)Figure Retrieval from Collections of Research ArticlesAdvances in Information Retrieval10.1007/978-3-030-15712-8_45(696-710)Online publication date: 7-Apr-2019
https://doi.org/10.1007/978-3-030-15712-8_45
Balog KBalog K(2018)Semantically Enriched Models for Entity RankingEntity-Oriented Search10.1007/978-3-319-93935-3_4(101-143)Online publication date: 3-Oct-2018
https://doi.org/10.1007/978-3-319-93935-3_4
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