Skip to main content
Top

2019 | OriginalPaper | Chapter

Temporal Information Retrieval and Its Application: A Survey

Authors : Rakshita Bansal, Monika Rani, Harish Kumar, Sakshi Kaushal

Published in: Emerging Research in Computing, Information, Communication and Applications

Publisher: Springer Singapore

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

With an advent of the Web, a tremendous amount of information is available online. Information can be organized and explored in the time dimension. This temporal information has to be distilled out, so as to extract the temporal entities such as temporal expressions and temporal relations out of it. Temporal information processing is an ongoing field of research that deals with natural language text, temporal relations, events or temporal queries. This paper presents a detailed analysis of the work carried out under temporal information retrieval (TIR) highlighting its subtasks like information extraction, indexing, ranking, query processing, clustering and classification. Also, it presents various challenges while dealing with temporal information. To the end, various application areas are elaborated such as temporal summarization, exploration and future event retrieval.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literature
3.
go back to reference Ingria, R., Saur, R., Pustejovsky, J., et al. (2002). TimeML: Robust specification of event and temporal expressions in text. In Proceedings of the AAAI Spring Symposium on New Directions in Question Answering (pp. 28–34). Ingria, R., Saur, R., Pustejovsky, J., et al. (2002). TimeML: Robust specification of event and temporal expressions in text. In Proceedings of the AAAI Spring Symposium on New Directions in Question Answering (pp. 28–34).
5.
go back to reference Pustejovsky, J., Lee, K., Bunt, H., & Romary, L. (2010). ISO-TimeML: An international standard for semantic annotation. In LREC, May 2010, La Valette, Malta. Pustejovsky, J., Lee, K., Bunt, H., & Romary, L. (2010). ISO-TimeML: An international standard for semantic annotation. In LREC, May 2010, La Valette, Malta.
6.
go back to reference Mani, I., & Wilson, G. (2000). Robust temporal processing of news. In Association for Computational Linguistics (pp. 69–76). Mani, I., & Wilson, G. (2000). Robust temporal processing of news. In Association for Computational Linguistics (pp. 69–76).
7.
go back to reference Negri, M., & Marseglia, L. (2005). Recognition and normalization of time expressions: ITC-irst at TERN 2004 (Tech. Report WP3.7, Information Society Technologies). Negri, M., & Marseglia, L. (2005). Recognition and normalization of time expressions: ITC-irst at TERN 2004 (Tech. Report WP3.7, Information Society Technologies).
8.
go back to reference Uzzaman, N., & Allen, J. F. (2010). TRIPS and TRIOS system for TempEval-2: Extracting temporal information from text. In Proceedings of the 5th International Workshop on Semantic Evaluation ACL (pp. 276–283). Uzzaman, N., & Allen, J. F. (2010). TRIPS and TRIOS system for TempEval-2: Extracting temporal information from text. In Proceedings of the 5th International Workshop on Semantic Evaluation ACL (pp. 276–283).
9.
go back to reference Chang, A. X., & Manning, C. D. (2012). SUTime: A library for recognizing and normalizing time expressions. In LREC (pp. 3735–3740). Chang, A. X., & Manning, C. D. (2012). SUTime: A library for recognizing and normalizing time expressions. In LREC (pp. 3735–3740).
10.
go back to reference Strötgen, J., & Gertz, M. (2010). HeidelTime high-quality rule-based extraction and normalization of temporal expressions. In Proceedings of the 5th International Workshop on Semantic Evaluation, ACL (pp. 321–324). Strötgen, J., & Gertz, M. (2010). HeidelTime high-quality rule-based extraction and normalization of temporal expressions. In Proceedings of the 5th International Workshop on Semantic Evaluation, ACL (pp. 321–324).
13.
go back to reference Bethard, S. (2013). ClearTK-TimeML: A minimalist approach to TempEval 2013. Seventh International Workshop on Semantic Evaluation, 2, 10–14. Bethard, S. (2013). ClearTK-TimeML: A minimalist approach to TempEval 2013. Seventh International Workshop on Semantic Evaluation, 2, 10–14.
14.
go back to reference Llorens, H., Saquete, E., & Navarro, B. (2010). Tipsem (English and Spanish): Evaluating crfs and semantic roles in tempeval-2. In Proceeding SemEval’10 Proceedings of the 5th International Workshop on Semantic Evaluation (pp. 284–291). Llorens, H., Saquete, E., & Navarro, B. (2010). Tipsem (English and Spanish): Evaluating crfs and semantic roles in tempeval-2. In Proceeding SemEval’10 Proceedings of the 5th International Workshop on Semantic Evaluation (pp. 284–291).
15.
go back to reference Tang, Y., Ye, X., & Tang, N. (2011). Temporal information processing technology and its application, Chap. 8, (pp. 51–158). Tang, Y., Ye, X., & Tang, N. (2011). Temporal information processing technology and its application, Chap. 8, (pp. 51–158).
17.
go back to reference Berberich, K., Bedathur, S., Neumann, T., & Weikum, G. (2007). A time machine for text search. In Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval —SIGIR’07, (pp. 519–526). https://doi.org/10.1145/1277741.1277831. Berberich, K., Bedathur, S., Neumann, T., & Weikum, G. (2007). A time machine for text search. In Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval —SIGIR’07, (pp. 519–526). https://​doi.​org/​10.​1145/​1277741.​1277831.
18.
go back to reference Berberich, K., Bedathur, S., Neumann, T., & Weikum, G. (2007). FluxCapacitor: Efficient time-travel text search. In Proceedings of the VLDB ’07 (pp. 1414–1417). Berberich, K., Bedathur, S., Neumann, T., & Weikum, G. (2007). FluxCapacitor: Efficient time-travel text search. In Proceedings of the VLDB ’07 (pp. 1414–1417).
19.
21.
go back to reference Anand, A., Bedathur, S., Berberich, K., & Schenkel, R. (2012). Index maintenance for time-travel text search. In Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval—SIGIR’12 (pp. 235–243). https://doi.org/10.1145/2348283.2348318. Anand, A., Bedathur, S., Berberich, K., & Schenkel, R. (2012). Index maintenance for time-travel text search. In Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval—SIGIR’12 (pp. 235–243). https://​doi.​org/​10.​1145/​2348283.​2348318.
23.
go back to reference Li, X., & Croft, W. B. (2003). Time-based language models. In Proceedings of the 12th International Conference on Information and Knowledge Management (pp. 469–475). Li, X., & Croft, W. B. (2003). Time-based language models. In Proceedings of the 12th International Conference on Information and Knowledge Management (pp. 469–475).
24.
go back to reference Jatowt, A., Kawai, Y., & Tanaka, K. (2005). Temporal ranking of search engine results. In Proceedings of the 6th International Conference on Web Information Systems Engineering (pp. 43–52). Jatowt, A., Kawai, Y., & Tanaka, K. (2005). Temporal ranking of search engine results. In Proceedings of the 6th International Conference on Web Information Systems Engineering (pp. 43–52).
25.
go back to reference Zhang, R., Chang, Y., & Zheng, Z. (2009). Search result re-ranking by feedback control adjustment for time-sensitive query. In Proceedings of NAACL HLT (pp. 165–168). Zhang, R., Chang, Y., & Zheng, Z. (2009). Search result re-ranking by feedback control adjustment for time-sensitive query. In Proceedings of NAACL HLT (pp. 165–168).
26.
go back to reference Strötgen, J., & Gertz, M. (2013). Proximity 2-aware ranking for textual, temporal, and geographic queries. In Proceedings of the 22nd ACM International Conference on Conference on Information & Knowledge Management—CIKM’13 (pp. 739–744). Strötgen, J., & Gertz, M. (2013). Proximity 2-aware ranking for textual, temporal, and geographic queries. In Proceedings of the 22nd ACM International Conference on Conference on Information & Knowledge Management—CIKM’13 (pp. 739–744).
27.
go back to reference Costa, M., Couto, F., & Silva, M. (2014). Learning temporal-dependent ranking models. In Proceedings of the 37th International ACM SIGIR Conference on Research & Development in Information Retrieval—SIGIR’14 (pp. 757–766). Costa, M., Couto, F., & Silva, M. (2014). Learning temporal-dependent ranking models. In Proceedings of the 37th International ACM SIGIR Conference on Research & Development in Information Retrieval—SIGIR’14 (pp. 757–766).
28.
31.
go back to reference Dakka, W., Gravano, L., & Ipeirotis, P. (2012). Answering general time-sensitive queries. IEEE Transactions on Knowledge and Data Engineering, 24(2), 220–235.CrossRef Dakka, W., Gravano, L., & Ipeirotis, P. (2012). Answering general time-sensitive queries. IEEE Transactions on Knowledge and Data Engineering, 24(2), 220–235.CrossRef
33.
go back to reference Alonso, O., & Gertz, M. (2006). Clustering of search results using temporal attributes. In Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval—SIGIR’06 (pp. 597–598). https://doi.org/10.1145/1148170.1148273. Alonso, O., & Gertz, M. (2006). Clustering of search results using temporal attributes. In Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval—SIGIR’06 (pp. 597–598). https://​doi.​org/​10.​1145/​1148170.​1148273.
35.
36.
go back to reference Jatowt, A., & Au Yeung, C. (2011). Extracting collective expectations about the future from large text collections. In Proceedings of the 20th ACM International Conference on Information and Knowledge Management—CIKM’11 (pp. 1259–1264). https://doi.org/10.1145/2063576.2063759. Jatowt, A., & Au Yeung, C. (2011). Extracting collective expectations about the future from large text collections. In Proceedings of the 20th ACM International Conference on Information and Knowledge Management—CIKM’11 (pp. 1259–1264). https://​doi.​org/​10.​1145/​2063576.​2063759.
37.
go back to reference Mani, I., Verhagen, M., Wellner, B., et al. (2006). Machine learning of temporal relations. In Proceedings of the 21st International Conference on Computational Linguistics and the 44th Annual Meeting of the ACL—ACL’06 (pp. 753–760). https://doi.org/10.3115/1220175.1220270. Mani, I., Verhagen, M., Wellner, B., et al. (2006). Machine learning of temporal relations. In Proceedings of the 21st International Conference on Computational Linguistics and the 44th Annual Meeting of the ACL—ACL’06 (pp. 753–760). https://​doi.​org/​10.​3115/​1220175.​1220270.
38.
go back to reference Chambers, N., Wang, S., & Jurafsky, D. (2007). Classifying temporal relations between events. In Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions (ACL’07), Association for Computational Linguistics, Stroudsburg, PA, USA (pp. 173–176). Chambers, N., Wang, S., & Jurafsky, D. (2007). Classifying temporal relations between events. In Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions (ACL’07), Association for Computational Linguistics, Stroudsburg, PA, USA (pp. 173–176).
39.
go back to reference UzZaman, N., & Allen, J. (2011). Temporal evaluation. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (pp. 351–356). UzZaman, N., & Allen, J. (2011). Temporal evaluation. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (pp. 351–356).
40.
go back to reference Souza, J. D., & Ng, V. (2013). Classifying temporal relations with rich linguistic knowledge. In Proceedings of NAACL HLT (pp. 918–927). Souza, J. D., & Ng, V. (2013). Classifying temporal relations with rich linguistic knowledge. In Proceedings of NAACL HLT (pp. 918–927).
41.
go back to reference Laokulrat, N., Miwa, M., Tsuruoka, Y., & Chikayama, T. (2013). Uttime: Temporal relation classification using deep syntactic features. In Proceedings of the Seventh International Workshop on Semantic Evaluation (pp. 88–92). Laokulrat, N., Miwa, M., Tsuruoka, Y., & Chikayama, T. (2013). Uttime: Temporal relation classification using deep syntactic features. In Proceedings of the Seventh International Workshop on Semantic Evaluation (pp. 88–92).
43.
go back to reference Campos, R., Dias, G., Jorge, A. M., & Nunes, C. (2014). C GTE-Cluster: A temporal search interface for implicit. In Proceedings of the European Conference on IR Research (pp. 775–779). Campos, R., Dias, G., Jorge, A. M., & Nunes, C. (2014). C GTE-Cluster: A temporal search interface for implicit. In Proceedings of the European Conference on IR Research (pp. 775–779).
45.
go back to reference Xu, T., Mcnamee, P., & Oard, D. W. (2013). HLTCOE at TREC 2013: Temporal summarization. In Proceedings of the 22nd Text Retrieval Conference (TREC’13). Xu, T., Mcnamee, P., & Oard, D. W. (2013). HLTCOE at TREC 2013: Temporal summarization. In Proceedings of the 22nd Text Retrieval Conference (TREC’13).
46.
47.
go back to reference Wang, B., Liakata, M., Tsakalidis, A., Kolaitis, S. G., Papadopoulos, S., Apostolidis, L., et al. (2017). TOTEMSS: Topic-based, temporal sentiment summarisation for Twitter. In Proceedings of the IJCNLP, System Demonstrations (pp. 21–24). Wang, B., Liakata, M., Tsakalidis, A., Kolaitis, S. G., Papadopoulos, S., Apostolidis, L., et al. (2017). TOTEMSS: Topic-based, temporal sentiment summarisation for Twitter. In Proceedings of the IJCNLP, System Demonstrations (pp. 21–24).
50.
go back to reference Zhang, S., Bahrampour, S., Ramakrishnan, N., Schott, L., & Shah, M. (2017). Deep learning on symbolic representations for large-scale heterogeneous time-series event prediction. In IEEE Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 5970–5974). Zhang, S., Bahrampour, S., Ramakrishnan, N., Schott, L., & Shah, M. (2017). Deep learning on symbolic representations for large-scale heterogeneous time-series event prediction. In IEEE Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 5970–5974).
Metadata
Title
Temporal Information Retrieval and Its Application: A Survey
Authors
Rakshita Bansal
Monika Rani
Harish Kumar
Sakshi Kaushal
Copyright Year
2019
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-13-6001-5_19