research-article

Identification of top relevant temporal expressions in documents

Authors:

Jannik Strötgen,

Michael GertzAuthors Info & Claims

TempWeb '12: Proceedings of the 2nd Temporal Web Analytics Workshop

Pages 33 - 40

https://doi.org/10.1145/2169095.2169102

Published: 17 April 2012 Publication History

Abstract

Temporal information is very common in textual documents, and thus, identifying, normalizing, and organizing temporal expressions is an important task in IR. Although there are some tools for temporal tagging, there is a lack in research focusing on the relevance of temporal expressions. Besides counting their frequency and verifying whether they satisfy a temporal search query, temporal expressions are often considered in isolation only. There are no methods to calculate the relevance of temporal expressions, neither in general nor with respect to a query.

In this paper, we present an approach to identify top relevant temporal expressions in documents using expression-, document-, corpus-, and query-based features. We present two relevance functions: one to calculate relevance scores for temporal expressions in general, and one with respect to a search query, which consists of a textual part, a temporal part, or both. Using two evaluation scenarios, we demonstrate the effectiveness of our approach.

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Cited By

Santana BCampos RAmorim EJorge ASilvano PNunes S(2023)A survey on narrative extraction from textual dataArtificial Intelligence Review10.1007/s10462-022-10338-756:8(8393-8435)Online publication date: 6-Jan-2023
https://doi.org/10.1007/s10462-022-10338-7
Zhang LJoho HYu H(2022)Semantic Modelling of Document Focus-Time for Temporal Information RetrievalCompanion Proceedings of the Web Conference 202210.1145/3487553.3524668(896-902)Online publication date: 25-Apr-2022
https://dl.acm.org/doi/10.1145/3487553.3524668
Campos RDuque JCândido TMendes JDias GJorge ANunes C(2021)Time-Matters: Temporal Unfolding of TextsAdvances in Information Retrieval10.1007/978-3-030-72240-1_53(492-497)Online publication date: 30-Mar-2021
https://doi.org/10.1007/978-3-030-72240-1_53
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Index Terms

Identification of top relevant temporal expressions in documents
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Language resources
2. Information systems
  1. Information retrieval
    1. Document representation
      1. Content analysis and feature selection

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Published In

cover image ACM Other conferences

TempWeb '12: Proceedings of the 2nd Temporal Web Analytics Workshop

April 2012

55 pages

ISBN:9781450311885

DOI:10.1145/2169095

Conference Chairs:
Ricardo Baeza-Yates
Yahoo! Research, Spain
,
Julien Masanès
Internet Memory Foundation, France and Netherlands
,
Marc Spaniol
Max-Planck-Institut für Informatik, Germany

Copyright © 2012 ACM.

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Association for Computing Machinery

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Publication History

Published: 17 April 2012

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TempWeb '12

TempWeb '12: 2nd Temporal Web Analytics Workshop

April 17, 2012

Lyon, France

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Cited By

Santana BCampos RAmorim EJorge ASilvano PNunes S(2023)A survey on narrative extraction from textual dataArtificial Intelligence Review10.1007/s10462-022-10338-756:8(8393-8435)Online publication date: 6-Jan-2023
https://doi.org/10.1007/s10462-022-10338-7
Zhang LJoho HYu H(2022)Semantic Modelling of Document Focus-Time for Temporal Information RetrievalCompanion Proceedings of the Web Conference 202210.1145/3487553.3524668(896-902)Online publication date: 25-Apr-2022
https://dl.acm.org/doi/10.1145/3487553.3524668
Campos RDuque JCândido TMendes JDias GJorge ANunes C(2021)Time-Matters: Temporal Unfolding of TextsAdvances in Information Retrieval10.1007/978-3-030-72240-1_53(492-497)Online publication date: 30-Mar-2021
https://doi.org/10.1007/978-3-030-72240-1_53
Jabeen SGao XAndreae P(2019)Semantic association computation: a comprehensive surveyArtificial Intelligence Review10.1007/s10462-019-09781-wOnline publication date: 20-Nov-2019
https://doi.org/10.1007/s10462-019-09781-w
Morbidoni CCucchiarelli AUrsino DDesai BFlesca SZumpano EMasciari ECaroprese L(2018)Leveraging linked entities to estimate focus time of short textsProceedings of the 22nd International Database Engineering & Applications Symposium10.1145/3216122.3216158(282-286)Online publication date: 18-Jun-2018
https://dl.acm.org/doi/10.1145/3216122.3216158
Di Martino SRomano SBertolotto MKanhabua NMazzeo ANejdl W(2017)Towards Exploiting Social Networks for Detecting Epidemic OutbreaksGlobal Journal of Flexible Systems Management10.1007/s40171-016-0148-y18:1(61-71)Online publication date: 11-Jan-2017
https://doi.org/10.1007/s40171-016-0148-y
Campos RDias GJorge ANunes C(2017)Identifying top relevant dates for implicit time sensitive queriesInformation Retrieval Journal10.1007/s10791-017-9302-120:4(363-398)Online publication date: 5-May-2017
https://doi.org/10.1007/s10791-017-9302-1
Hürriyetoǧlu AOostdijk Nvan den Bosch A(2017)Estimating Time to Event of Future Events Based on Linguistic Cues on TwitterIntelligent Natural Language Processing: Trends and Applications10.1007/978-3-319-67056-0_5(67-97)Online publication date: 18-Nov-2017
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Rizzo SMontesi D(2017)Temporal Feature Space for Text ClassificationText, Speech, and Dialogue10.1007/978-3-319-64206-2_41(362-370)Online publication date: 29-Jul-2017
https://doi.org/10.1007/978-3-319-64206-2_41
Whiting SJose JAlonso OPerego RSebastiani FAslam JRuthven IZobel J(2016)SOGOU-2012-CRAWLProceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval10.1145/2911451.2914668(709-712)Online publication date: 7-Jul-2016
https://dl.acm.org/doi/10.1145/2911451.2914668
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