Skip to main content
SpringerLink
Log in

The Role of Computational Intelligence in Temporal Information Retrieval: A Survey of Imperfect Time in Information Systems

  • Conference paper
  • First Online:
Flexible Query Answering Systems 2015

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 400))

Abstract

In existing literature, many proposals have concerned the modeling or handling of imperfection in time in information systems. However, although reviews, surveys and overviews about either imperfection or time in information systems exist, no reviews, surveys or overviews about imperfection in time in information systems seem to exist. The main contribution of the work presented in this paper is to attempt to fill this void by presenting a survey of some existing scientific contributions dealing with time in information systems. A more modest contribution is an attempt at identifying some open research challenges or opportunities concerning imperfection in time in information systems.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aigner, W., Miksch, S., Thurnher, B., Biffl, S.: Planninglines: Novel glyphs for representing temporal uncertainties and their evaluation. In: Proceedings of the 9th International Conference on Information Visualisation, pp. 457–463 (2005)

    Google Scholar 

  2. Allen, J.F.: Maintaining knowledge about temporal intervals. Communications of the ACM 26(11), 832–843 (1983)

    Article  MATH  Google Scholar 

  3. Allen, J.F.: Towards a general theory of action and time. Artificial Intelligence 23(2), 123–154 (1984)

    Article  MATH  Google Scholar 

  4. Allen, J.F.: Time and time again: The many ways to represent time. International Journal of Intelligent Systems 6(4), 341–355 (1991)

    Article  Google Scholar 

  5. Alonso, O., Strötgen, J., Baeza-Yates, R., Gertz, M.: Temporal information retrieval: challenges and opportunities. In: Proceedings of the 1st International Temporal Web Analytics Workshop, vol. i, pp. 1–8, Hyderabad, India (2011)

    Google Scholar 

  6. Anselma, L., Terenziani, P., Snodgrass, R.T.: Valid-time indeterminacy in temporal relational databases: A family of data models. In: 17th International Symposium on Temporal Representation and Reasoning, pp. 139–145, Paris, France (2010)

    Google Scholar 

  7. Arotaritei, D., Mitra, S.: Web mining: a survey in the fuzzy framework. Fuzzy Sets and Systems 148(1), 5–19 (2004)

    Article  MathSciNet  Google Scholar 

  8. Asmussen, K., Qiang, Y., De Maeyer, P., Van De Weghe, N.: Triangular models for studying and memorising temporal knowledge. In: Proceedings of the International Conference on Education, Research and Innovation, pp. 1849–1859. IATED, Madrid (2009)

    Google Scholar 

  9. Badaloni, S., Giacomin, M.: A fuzzy extension of allen’s interval algebra. In: Lamma, E., Mello, P. (eds.) AI*IA 1999. LNCS (LNAI), vol. 1792, pp. 155–165. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  10. Badaloni, S., Giacomin, M.: The algebra ia fuz: a framework for qualitative fuzzy temporal reasoning. Artificial Intelligence 170, 872–908 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  11. Bassiri, A., Malek, M.R., Alesheikh, A.A., Amirian, P.: Temporal relationships between rough time intervals. In: Gervasi, O., Taniar, D., Murgante, B., Laganà, A., Mun, Y., Gavrilova, M.L. (eds.) ICCSA 2009, Part I. LNCS, vol. 5592, pp. 543–552. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  12. van Beek, P.: Temporal query processing with indefinite information. Artificial Intelligence in Medicine 3(6), 325–339 (1991)

    Article  Google Scholar 

  13. Billiet, C., De Tré, G.: Combining uncertainty and vagueness in time intervals. In: Angelov, P. (ed.) Intelligent Systems 2014. AISC, vol. 322, pp. 353–364. Springer, Heidelberg (2014)

    Google Scholar 

  14. Billiet, C., De Tré, G.: Twodimensional visualization of discrete time domain intervals subject to uncertainty. In: Proceedings of the 6th International Conference on Fuzzy Computation Theory and Applications, pp. 137–145. Scitepress, Rome (2014)

    Google Scholar 

  15. Billiet, C., Pons, J.E., Matthé, T., De Tré, G., Pons Capote, O.: Bipolar fuzzy querying of temporal databases. In: Christiansen, H., De Tré, G., Yazici, A., Zadrozny, S., Andreasen, T., Larsen, H.L. (eds.) FQAS 2011. LNCS, vol. 7022, pp. 60–71. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  16. Billiet, C., Pons, J.E., Pons Capote, O., De Tré, G.: Evaluating possibilistic valid-time queries. In: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., Yager, R.R. (eds.) IPMU 2012, Part I. CCIS, vol. 297, pp. 410–419. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  17. Billiet, C., Pons Frias, J.E., Pons, O., De Tré, G.: Bipolarity in the Querying of Temporal Databases, pp. 21–37. SRI PAS/IBS PAN, new trends edn. (2013)

    Google Scholar 

  18. Billiet, C., Pons, J.E., Pons, O., De Tré, G.: Bipolar querying of valid-time intervals subject to uncertainty. In: Larsen, H.L., Martin-Bautista, M.J., Vila, M.A., Andreasen, T., Christiansen, H. (eds.) FQAS 2013. LNCS, vol. 8132, pp. 401–412. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  19. Billiet, C., Pons Frias, J.E., Pons Capote, O., De Tré, G.: A comparison of approaches to model uncertainty in time intervals. In: Advances in Intelligent Systems Research, pp. 626–633. Atlantis Press, Milano (2013)

    Google Scholar 

  20. Bittner, T.: Approximate qualitative temporal reasoning. Annals of Mathematics and Artificial Intelligence 36(1–2), 39–80 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  21. Black, M.: Vagueness. an exercise in logical analysis. Philosophy of Science 4(4), 427–455 (1937)

    Article  Google Scholar 

  22. Jensen, C.S., et al.: The consensus glossary of temporal database concepts - february 1998 version. In: Etzion, O., Jajodia, S., Sripada, S. (eds.) Dagstuhl Seminar 1997. LNCS, vol. 1399, pp. 367–405. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  23. Bolour, A., Anderson, T.L., Dekeyser, L.J., Wong, H.K.T.: The role of time in information processing: A survey. ACM SIGART Bulletin 80, 28–46 (1982)

    Article  Google Scholar 

  24. Bordogna, G., Bucci, F., Carrara, P., Pagani, M., Rampini, A.: Extending inspire metadata to imperfect temporal descriptions. International Journal of Spatial Data Infrastructures Research, Special Issue GSDI-11 (2009)

    Google Scholar 

  25. Bordogna, G., Carrara, P., Pagani, M., Pepe, M., Rampini, A.: Managing imperfect temporal metadata in the catalog services of spatial data infrastructures compliant with inspire. In: Proceedings of the Joint 2009 International Fuzzy Systems Associations World Congress and 2009 European Society of Fuzzy Logic and Technology Conference, pp. 915–920, Lisbon, Portugal (2009)

    Google Scholar 

  26. Bosc, P., Kraft, D., Petry, F.: Fuzzy sets in database and information systems: Status and opportunities. Fuzzy Sets and Systems 156(3), 418–426 (2005)

    Article  MathSciNet  Google Scholar 

  27. Bosc, P., Pivert, O.: Modeling and querying uncertain relational databases: A survey of approaches based on the possible worlds semantics. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 18(5), 565–603 (2010)

    Article  MathSciNet  Google Scholar 

  28. Bosch, A., Torres, M., Marín, R.: Reasoning with disjunctive fuzzy temporal constraint networks. In: Proceedings of the 9th International Symposium on Temporal Representation and Reasoning, pp. 36–43. IEEE (2002)

    Google Scholar 

  29. Bronselaer, A., Pons, J.E., De Tré, G., Pons, O.: Possibilistic evaluation of sets. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 21(3), 325–346 (2013)

    Article  MathSciNet  Google Scholar 

  30. Chountas, P., Petrounias, I.: Modelling and representation of uncertain temporal information. Requirements Engineering 5(3), 144–156 (2000)

    Article  MATH  Google Scholar 

  31. De Caluwe, R., Devos, F., Maesfranckx, P., De Tré, G., Van Der Cruyssen, B.: The Semantics and Modelling of Flexible Time Indications. Studies in Fuzziness and Soft Computing, chap. 11, pp. 229–256. Springer (1999)

    Google Scholar 

  32. De Tré, G., Bronselaer, A.J., Billiet, C., Qiang, Y., Van De Weghe, N., De Maeyer, P., Pons, J.E., Pons, O.: Visualising and handling uncertain time intervals in a two-dimensional triangular space. In: Proceedings of the Second World Conference on Soft Computing, pp. 585–592, Baku, Azerbaijan (2012)

    Google Scholar 

  33. De Tré, G., De Caluwe, R., Van Der Cruyssen, B.: Dealing with time in fuzzy and uncertain object-oriented database models. In: Proceedings of the EUFIT 97 Conference, pp. 1157–1161, Aachen, Germany (1997)

    Google Scholar 

  34. De Tré, G., Van de Weghe, N., de Caluwe, R., De Maeyer, P.: Towards a flexible visualization tool for dealing with temporal data. In: Larsen, H.L., Pasi, G., Ortiz-Arroyo, D., Andreasen, T., Christiansen, H. (eds.) FQAS 2006. LNCS (LNAI), vol. 4027, pp. 109–120. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  35. Dekhtyar, A., Ozcan, F., Ross, R., Subrahmanian, V.S.: Probabilistic temporal databases, ii: Calculus and query processing (2001)

    Google Scholar 

  36. Dekhtyar, A., Ross, R., Subrahmanian, V.S.: Probabilistic temporal databases, i: Algebra. ACM Transactions on Database Systems 26(1), 41–95 (2001)

    Article  MATH  Google Scholar 

  37. Dubois, D., Esteva, F., Godo, L., Prade, H.: An Information-based Discussion of Vagueness: Six Scenarios Leading to Vagueness, chap. 40, pp. 891–909. Elsevier (2005)

    Google Scholar 

  38. Dubois, D., Fargier, H., Galvagnon, V.: On latest starting times and floats in activity networks with ill-known durations. European Journal Of Operational Research 147, 266–280 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  39. Dubois, D., HadjAli, A., Prade, H.: Fuzziness and uncertainty in temporal reasoning. Journal of Universal Computer Science 9(9), 1168–1194 (2003)

    MathSciNet  Google Scholar 

  40. Dubois, D., Hadjali, A., Prade, H.: A possibility theory-based approach to the handling of uncertain relations between temporal points. International Journal of Intelligent Systems 22(2), 157–179 (2007)

    Article  MATH  Google Scholar 

  41. Dubois, D., Lang, J., Prade, H.: Timed possibilistic logic. Fundamenta Informaticae 15(3–4), 211–234 (1991)

    MathSciNet  MATH  Google Scholar 

  42. Dubois, D., Prade, H.: Processing fuzzy temporal knowledge. IEEE Transactions on Systems, Man and Cybernetics 19(4), 729–744 (1989)

    Article  MathSciNet  Google Scholar 

  43. Dubois, D., Prade, H.: Formal representations of uncertainty. In: Decision-Making Process: Concepts and Methods, chap. 3, p. 59. Wiley, London (2009)

    Google Scholar 

  44. Dubois, D., Prade, H.: Gradualness, uncertainty and bipolarity: Making sense of fuzzy sets. Fuzzy Sets and Systems 192(1), 3–24 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  45. Dyreson, C.E., et al.: A consensus glossary of temporal database concepts. SIGMOD Record 23(1), 52–64 (1994)

    Article  Google Scholar 

  46. Dyreson, C.E., Snodgrass, R.T.: Supporting valid-time indeterminacy. ACM Transactions on Database Systems 23(1), 1–57 (1998)

    Article  Google Scholar 

  47. Freksa, C.: Temporal reasoning based on semi-intervals. Artificial Intelligence 54(1–2), 199–227 (1992)

    Article  MathSciNet  Google Scholar 

  48. Galindo, J., Medina, J.M.: Ftsql2: Fuzzy time in relational databases*. In: Proceedings of the 2nd International Conference in Fuzzy Logic and Technology, pp. 47–50. Leicester (2001)

    Google Scholar 

  49. Galton, A.: A critical examination of allen’s theory of action and time. Artificial Intelligence 42(2–3), 159–188 (1990)

    Article  MathSciNet  MATH  Google Scholar 

  50. Garrido, C., Marín, N., Pons, O.: Fuzzy intervals to represent fuzzy valid time in a temporal relational database. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 17(Suppl. 1), 173–192 (2009)

    Article  MATH  Google Scholar 

  51. Godo, L., Vila, L.: Possibilistic temporal reasoning based on fuzzy temporal constraints. In: Proceedings of the 14th International Joint Conference on Artificial Intelligence, pp. 1916–1922. Morgan Kaufmann, Montréal (1995)

    Google Scholar 

  52. Guil, F., Bosch, A., Bailón, A., Marín, R.: A fuzzy approach for mining generalized frequent temporal patterns. In: Proceedings of the 4th IEEE International Conference on Data Mining, Workshop on Alternative Techniques for Data Mining and Knowledge Discovery, p. 6. IEEE Computer Society, Washington, DC (2004)

    Google Scholar 

  53. Kacprzyk, J., Zadrozny, S.: Computing with words in intelligent database querying: Standalone and internet-based applications. Information Sciences 134(1–4), 71–109 (2001)

    Article  MATH  Google Scholar 

  54. Kahn, K., Gorry, G.A.: Mechanizing temporal knowledge. Artificial Intelligence 9(1), 87–108 (1977)

    Article  Google Scholar 

  55. Kalczynski, P.J., Chou, A.: Temporal document retrieval model for business news archives. Information Processing & Management 41, 635–650 (2005)

    Article  Google Scholar 

  56. Kolmogorov, A.: Grundbegriffe der Wahrscheinlichkeitsrechnung. Julius Springer, Berlin (1933)

    Book  Google Scholar 

  57. Kopetz, H., Kim, K.H.K.: Temporal uncertainties in interactions among real-time objects. In: Proceedings of the 9th Symposium on Reliable Distributed Systems, pp. 165–174, Huntsville, U.S.A (1990)

    Google Scholar 

  58. Koubarakis, M.: Database models for infinite and indefinite temporal information. Information Systems 19(2), 141–173 (1994)

    Article  Google Scholar 

  59. Long, W.: Temporal reasoning for diagnosis in a causal probabilistic knowledge base. Artificial Intelligence in Medicine 8(3), 193–215 (1996)

    Article  Google Scholar 

  60. Mitra, D., Gerard, M.L., Srinivasan, P., Hands, A.E.: A possibilistic interval constraint problem: Fuzzy temporal reasoning. In: Proceedings of the 3rd IEEE Conference on Fuzzy Systems, pp. 1434–1439 (1994)

    Google Scholar 

  61. Motro, A., Smets, P.: Uncertainty Management in Information Systems: from Needs to Solutions. Kluwer Academic Publishers (1997)

    Google Scholar 

  62. Nagypál, G., Motik, B.: A fuzzy model for representing uncertain, subjective, and vague temporal knowledge in ontologies. In: Meersman, R., Schmidt, D.C. (eds.) CoopIS 2003, DOA 2003, and ODBASE 2003. LNCS, vol. 2888, pp. 906–923. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  63. O’Connor, M.J., Tu, S.W., Musen, M.A.: Representation of temporal indeterminacy in clinical databases. In: Proceedings of the AMIA Symposium, pp. 615–619 (2000)

    Google Scholar 

  64. Palma, J., Juarez, J.M., Campos, M., Marin, R.: A fuzzy approach to temporal model-based diagnosis for intensive care units. In: Proceedings of the 16th European Conference on Artificial Intelligence, pp. 868–872. Amsterdam, The Netherlands (2004)

    Google Scholar 

  65. Palma, J., Juarez, J.M., Campos, M., Marin, R.: Fuzzy theory approach for temporal model-based diagnosis : An application to medical domains. Artificial Intelligence in Medicine (2006)

    Google Scholar 

  66. Pani, A.K., Bhattacharjee, G.P.: Temporal representation and reasoning in artificial intelligence: A review. Mathematical and Computer Modelling 34, 55–80 (2001)

    Article  MATH  Google Scholar 

  67. Parsons, S.: Current approaches to handling imperfect information in data and knowledge bases. IEEE Transactions on Knowledge and Data Engineering 8(3), 353–372 (1996)

    Article  Google Scholar 

  68. Pons, J.E., Billiet, C., Pons Capote, O., De Tré, G.: A possibilistic valid-time model. In: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., Yager, R.R. (eds.) IPMU 2012, Part I. CCIS, vol. 297, pp. 420–429. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  69. Pons, J.E., Marín, N., Pons, O., Billiet, C., Tré, G.D.: A relational model for the possibilistic valid-time approach. International Journal of Computational Intelligence Systems 5(6), 1068–1088 (2012)

    Article  Google Scholar 

  70. Pons Frias, J.E., Billiet, C., Pons, O., De Tré, G.: Aspects of dealing with imperfect data in temporal databases. In: Pivert, O., Zadroźny, S. (eds.) Flexible Approaches in Data, Information and Knowledge Management. ACI, vol. 497, pp. 189–220. Springer, Heidelberg (1991)

    Chapter  Google Scholar 

  71. Qiang, Y.: Modelling Temporal Information in a Two-dimensional Space - A Visualization Perspective. Phd thesis, Ghent University (2012)

    Google Scholar 

  72. Qiang, Y., Asmussen, K., Delafontaine, M., Stichelbaut, B., De Tré, G., De Maeyer, P., Van De Weghe, N.: Visualising rough time intervals in a two-dimensional space. In: Proceedings of IFSA World Congress/EUSFLAT Conference, pp. 1480–1485 (2009)

    Google Scholar 

  73. Qiang, Y., Delafontaine, M., Asmussen, K., Stichelbaut, B., De Maeyer, P., Van De Weghe, N.: Modelling imperfect time intervals in a two-dimensional space*. Control And Cybernetics 39(4), 983–1010 (2010)

    MATH  Google Scholar 

  74. Researchers, T.D.S.: Summaries of current work. In: Temporal Databases: Research and Practice, pp. 414–428. Springer (1998)

    Google Scholar 

  75. Ryabov, V.: Uncertain relations between indeterminate temporal intervals. In: Proceedings of The 10th International Conference on Management of Data, pp. 87–95. Tata McGraw-Hill Publishing Company, New Delhi (2000)

    Google Scholar 

  76. Ryabov, V.: Probabilistic estimation of uncertain temporal relations. Revista Colombiana de Computacion 2(2) (2001)

    Google Scholar 

  77. Ryabov, V., Terziyan, V.: Industrial diagnostics using algebra of uncertain temporal relations. In: Proceedings of the 21st International Multi-Conference on Applied Informatics, pp. 351–356. ACTA Press, Innsbruck (2003)

    Google Scholar 

  78. Ryabov, V., Trudel, A.: Probabilistic temporal interval networks. In: Proceedings of the 11th International Symposium on Temporal Representation and Reasoning, pp. 64–67 (2004)

    Google Scholar 

  79. Schockaert, S., Cock, M.D.: Temporal reasoning about fuzzy intervals. Artificial Intelligence 172, 1158–1193 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  80. Schockaert, S., De Cock, M., Kerre, E.E.: Imprecise temporal interval relations. In: Bloch, I., Petrosino, A., Tettamanzi, A.G.B. (eds.) WILF 2005. LNCS (LNAI), vol. 3849, pp. 108–113. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  81. Schockaert, S., De Cock, M., Kerre, E.E.: Fuzzifying allens tempora interval relations. IEEE Transactions on Fuzzy Systems 16(2), 517–533 (2008)

    Article  Google Scholar 

  82. Tossebro, E., Nygard, M.: Uncertainty in spatiotemporal databases. In: Yakhno, T. (ed.) ADVIS 2002. AIS, vol. 2457, pp. 43–53. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  83. Trajcevski, G.: Probabilistic range queries in moving objects databases with uncertainty. In: Proceedings of the 3rd ACM International Workshop on Data Engineering for Wireless and Mobile Access, pp. 39–45. ACM (2003)

    Google Scholar 

  84. Vila, L.: A survey on temporal reasoning in artificial intelligence. AI Communications 7(1), 4–28 (1994)

    Google Scholar 

  85. Virant, J., Zimic, N.: Attention to time in fuzzy logic. Fuzzy Sets and Systems 82(1), 39–49 (1996)

    Article  MathSciNet  Google Scholar 

  86. Wu, Y., Jajodia, S., Wang, X.S.: Temporal database bibliography update. In: Etzion, O., Jajodia, S., Sripada, S. (eds.) Dagstuhl Seminar 1997. LNCS, vol. 1399, pp. 338–366. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  87. Zadeh, L.A.: Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems 1(1), 3–28 (1978)

    Article  MathSciNet  MATH  Google Scholar 

  88. Zadeh, L.A.: The role of fuzzy logic in the management of uncertainty in expert systems. Fuzzy Sets and Systems 11, 199–227 (1983)

    Article  MathSciNet  MATH  Google Scholar 

  89. Zhang, H., Diao, Y., Immerman, N.: Recognizing patterns in streams with imprecise timestamps. Proceedings of the VLDB Endowment 3(1–2), 244–255 (2010)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Telecommunications and Information Processing, Ghent University, Sint-Pietersnieuwstraat 41, 9000, Ghent, Belgium

    Christophe Billiet & Guy De Tré

Authors
  1. Christophe Billiet
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guy De Tré
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Christophe Billiet .

Editor information

Editors and Affiliations

  1. Dept. of Comm., Business & Info. Tech., Roskilde University, Roskilde, Denmark

    Troels Andreasen

  2. Dept. Computer Science, Roskilde University, Roskilde, Denmark

    Henning Christiansen

  3. Sys Res Intit of Polish Acad of Science, Intelligent Systems Laboratory, Warsaw, Poland

    Janusz Kacprzyk

  4. Department of Electronic Systems, Aalborg University, Esbjerg, Denmark

    Henrik Larsen

  5. Computer Science Department, University Milano-Biccoca, Milano, Italy

    Gabriella Pasi

  6. IRISA, University of Rennes I, Rennes, France

    Olivier Pivert

  7. Dept. of Tele. & Info. Processing, Ghent University, Gent, Belgium

    Guy De Tré

  8. Dept. of Comp. & Art. Int. Sci., University of Granada, Granada, Spain

    Maria Amparo Vila

  9. Department of Computer Engineering, Middle East Technical University, Ankara, Turkey

    Adnan Yazici

  10. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Sławomir Zadrożny

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Billiet, C., De Tré, G. (2016). The Role of Computational Intelligence in Temporal Information Retrieval: A Survey of Imperfect Time in Information Systems. In: Andreasen, T., et al. Flexible Query Answering Systems 2015. Advances in Intelligent Systems and Computing, vol 400. Springer, Cham. https://doi.org/10.1007/978-3-319-26154-6_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-26154-6_4

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26153-9

  • Online ISBN: 978-3-319-26154-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation