An Information Retrieval Ontology for Information Retrieval Nanopublications

  • Aldo Lipani
  • Florina Piroi
  • Linda Andersson
  • Allan Hanbury
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8685)

Abstract

Retrieval experiments produce plenty of data, like various experiment settings and experimental results, that are usually not all included in the published articles. Even if they are mentioned, they are not easily machine-readable. We propose the use of IR nanopublications to describe in a formal language such information. Furthermore, to support the unambiguous description of IR domain aspects, we present a preliminary IR ontology. The use of the IR nanopublications will facilitate the assessment and comparison of IR systems and enhance the degree of reproducibility and reliability of IR research progress.

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References

  1. 1.
    Guidelines for nanopublication, http://nanopub.org/guidelines/working_draft/ (last retrieved: May 2014)
  2. 2.
    Allen, J.: Natural Language Understanding, 2nd edn. Benjamin-Cummings Publishing Co., Inc., Redwood City (1995)MATHGoogle Scholar
  3. 3.
    Buckheit, J., Donoho, D.L.: Wavelab and Reproducible Research. In: Wavelets and Statistics. Springer, Berlin (1995)Google Scholar
  4. 4.
    Fernàndez, M., Cantador, I., Lòpez, V., Vallet, D., Castells, P., Motta, E.: Semantically enhanced Information Retrieval: An ontology-based approach. J. Web Semant. 9(4), 434–452 (2011)CrossRefGoogle Scholar
  5. 5.
    Frantzi, K., Ananiadou, S., Mima, H.: Automatic recognition of multi-word terms: the C-value/NC-value method. Int. J. Digit. Libr. 3(2), 115–130 (2000)CrossRefGoogle Scholar
  6. 6.
    Freire, J., Bonnet, P., Shasha, D.: Computational Reproducibility: State-of-the-art, Challenges, and Database Research Opportunities. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, SIGMOD 2012, pp. 593–596. ACM, New York (2012)CrossRefGoogle Scholar
  7. 7.
    Gómez-Pérez, A., Fernandez-Lopez, M., Corcho, O.: Ontological engineering, vol. 139. Springer (2004)Google Scholar
  8. 8.
    Groth, P., Gibson, A., Velterop, J.: The Anatomy of a Nanopublication. Inf. Serv. Use 30(1-2), 51–56 (2010)Google Scholar
  9. 9.
    Harman, D.: Information retrieval evaluation. Synthesis Lectures on Information Concepts, Retrieval, and Services 3(2), 1–119 (2011)CrossRefGoogle Scholar
  10. 10.
    Li, Z., Raskin, V., Ramani, K.: Developing Engineering Ontology for Information Retrieval. J. Comput. Inform. Sci. Eng. (2008)Google Scholar
  11. 11.
    Manning, C.D., Raghavan, P., Schütze, H.: Introduction to Information Retrieval. Cambridge University Press, New York (2008)CrossRefMATHGoogle Scholar
  12. 12.
    Robertson, S.: On the history of evaluation in IR. J. Inform. Sci. 34(4), 439–456 (2008)CrossRefGoogle Scholar
  13. 13.
    Roelleke, T.: Information Retrieval Models: Foundations and Relationships. Synthesis Lectures on Information Concepts, Retrieval, and Services 5(3), 1–163 (2013)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Aldo Lipani
    • 1
  • Florina Piroi
    • 1
  • Linda Andersson
    • 1
  • Allan Hanbury
    • 1
  1. 1.Institute of Software Technology and Interactive Systems (ISIS)Vienna University of TechnologyAustria

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