Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Time and Information Retrieval

  • Omar Alonso
  • Michael Gertz
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_929

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...

This is a preview of subscription content, log in to check access.

Recommended Reading

  1. 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.Google Scholar
  2. 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.Google Scholar
  3. 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.Google Scholar
  4. 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.Google Scholar
  5. 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.CrossRefGoogle Scholar
  6. 6.
    Mani I, Pustejovsky J, Gaizauskas RJ, editors. The language of time. Oxford: Oxford University Press; 2005.Google Scholar
  7. 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.Google Scholar
  8. 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.Google Scholar
  9. 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.Google Scholar
  10. 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.Google Scholar
  11. 11.
    Strötgen J, Gertz M. Multilingual and cross-domain temporal tagging. Lang Resour Eval. 2013;47(2):269–298. Springer.Google Scholar
  12. 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.Google Scholar
  13. 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.Google Scholar
  14. 14.
    TimeML. Markup language for temporal and event expressions. http://www.timeml.org/
  15. 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.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Microsoft Silicon ValleyMountain ViewUSA
  2. 2.Heidelberg UniversityHeidelbergGermany