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Time and Information Retrieval

  • Reference work entry
  • First Online:
Encyclopedia of Database Systems

  • 11 Accesses

Synonyms

Temporal information retrieval

Definition

Traditional information retrieval (IR) is concerned with models, algorithms, and architectures for the retrieval and ranking of documents from a document collection based on their relevance to search queries. In temporal information retrieval, expressions (words or phrases) that relate to instants in time, events, time periods, or other temporal descriptions are extracted from documents and handled in a special way to rank (and optionally group) the documents returned for a search query. Thus, in temporal information retrieval, temporal expressions extracted from documents play a special role in the overall relevance and in the organization and exploration of search results along timelines.

Historical Background

Research on temporal annotations has gained a lot of attention lately, and it is covered in great depth in the book edited by Mani et al. [6]. The work also includes discussions about tense and structural analysis and temporal...

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Recommended Reading

  1. Allan J, Gupta R, Khandelwal V. Temporal summaries of news topics. In: Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval; 2001. p. 10–18.

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  2. Alonso O, Baeza-Yates R, Gertz M. Clustering and exploring search results using timeline constructions. In: Proceedings of the 18th ACM International Conference on Information and Knowledge Management; 2009. p. 97–106.

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  3. Berberich K, Bedathur SJ, Alonso O, Weikum G. A language modeling approach for temporal information needs. In: Proceedings of the 30th European Conference on IR Research; 2010. p. 13–25.

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  4. Diaz F, Hauff C, Murdock V, de Rijke M, Shokouhi M. SIGIR 2014 workshop on temporal, social and spatially-aware information access (#TAIA2014). In: Proceedings of the 37th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval; 2014. p. 1298.

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  5. Mani I, Pustejovsky J, Sundheim B. Introduction to the special issue on temporal information processing. ACM Trans Asian Lang Inf Process. 2004;3(1):1–10.

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  6. Mani I, Pustejovsky J, Gaizauskas RJ, editors. The language of time. Oxford: Oxford University Press; 2005.

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  7. Ringel M, Cutrell E, Dumais ST, Horvitz E. Milestones in time: the value of landmarks in retrieving information from personal stores. In: Proceedings of the IFIP TC13 International Conference on Human-Computer Interaction; 2003. p. 184–91.

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  8. Schilder F, Habel C. From temporal expressions to temporal information: semantic tagging of news messages. In: Proceedings of the ACL 2001 Workshop on Temporal and Spatial Information Processing; 2001.

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  9. Shaparenko B, Caruana R, Gehrke J, Joachims T. Identifying temporal patterns and key players in document collections. In: Proceedings of the IEEE ICDM Workshop on Temporal Data Mining: Algorithms, Theory and Applications (TDM-05); 2005. p. 165–74.

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  10. Spaniol M, Masans J, Baeza-Yates RA. The 4th Temporal Web Analytics Workshop (TempWeb’14). In: Proceedings of the 23rd International World Wide Web Conference; 2014. p. 863–64.

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  11. Strötgen J, Gertz M. Multilingual and cross-domain temporal tagging. Lang Resour Eval. 2013;47(2):269–298. Springer.

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  12. Strötgen J, Zell J, Gertz M. HeidelTime: tuning english and developing spanish resources for tempEval-3. In: Proceedings of the 7th International Workshop on Semantic Evaluation; 2013.

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  13. Swan R, Allan J. Automatic generation of overview timelines. In: Proceedings of the 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval; 2000. p. 49–56.

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  14. TimeML. Markup language for temporal and event expressions. http://www.timeml.org/

  15. Yeung C-MA, Jatowt A. Studying how the past is remembered: towards computational history through large scale text mining. In: Proceedings of the 20th ACM International Conference on Information and Knowledge Management; 2011. p. 1231–40.

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Author information

Authors and Affiliations

  1. Microsoft Silicon Valley, Mountain View, CA, USA

    Omar Alonso

  2. Heidelberg University, Heidelberg, Germany

    Michael Gertz

Authors
  1. Omar Alonso
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  2. Michael Gertz
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Corresponding author

Correspondence to Omar Alonso .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, GA, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, ON, Canada

    M. Tamer Özsu

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Alonso, O., Gertz, M. (2018). Time and Information Retrieval. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_929

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