Skip to main content

A Visual Interactive Environment for Making Sense of Experimental Data

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNISA,volume 8416)

Abstract

We present the Visual Information Retrieval Tool for Upfront Evaluation (VIRTUE) which is an interactive and visual system supporting two relevant phases of the experimental evaluation process: performance analysis and failure analysis.

Keywords

  • Failure Analysis
  • Information Retrieval System
  • Result List
  • Optimal Ranking
  • Ranking Evaluation

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-319-06028-6_92
  • Chapter length: 4 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   109.00
Price excludes VAT (USA)
  • ISBN: 978-3-319-06028-6
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   149.99
Price excludes VAT (USA)

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Angelini, M., Ferro, N., Järvelin, K., Keskustalo, H., Pirkola, A., Santucci, G., Silvello, G.: Cumulated Relative Position: A Metric for Ranking Evaluation. In: Catarci, T., Forner, P., Hiemstra, D., Peñas, A., Santucci, G. (eds.) CLEF 2012. LNCS, vol. 7488, pp. 112–123. Springer, Heidelberg (2012)

    CrossRef  Google Scholar 

  2. Angelini, M., Ferro, N., Santucci, G., Silvello, G.: Visual Interactive Failure Analysis: Supporting Users in Information Retrieval Evaluation. In: Proc. 4th Symposium on Information Interaction in Context (IIiX 2012), pp. 195–203. ACM Press, New York (2012)

    Google Scholar 

  3. Angelini, M., Ferro, N., Santucci, G., Silvello, G.: Improving Ranking Evaluation Employing Visual Analytics. In: Forner, P., Müller, H., Paredes, R., Rosso, P., Stein, B. (eds.) CLEF 2013. LNCS, vol. 8138, pp. 29–40. Springer, Heidelberg (2013)

    CrossRef  Google Scholar 

  4. Angelini, M., Ferro, N., Santucci, G., Silvello, G.: VIRTUE: A Visual Tool for Information Retrieval Performance Evaluation and Failure Analysis. Journal of Visual Languages & Computing (in print, 2014)

    Google Scholar 

  5. Di Buccio, E., Dussin, M., Ferro, N., Masiero, I., Santucci, G., Tino, G.: To Re-rank or to Re-query: Can Visual Analytics Solve This Dilemma? In: Forner, P., Gonzalo, J., Kekäläinen, J., Lalmas, M., de Rijke, M. (eds.) CLEF 2011. LNCS, vol. 6941, pp. 119–130. Springer, Heidelberg (2011)

    CrossRef  Google Scholar 

  6. Harman, D.K.: Some thoughts on failure analysis for noisy data. In: Proc. 2nd Workshop on Analytics for Noisy unstructured text Data (AND 2008), p. 1. ACM Press, New York (2008)

    CrossRef  Google Scholar 

  7. Järvelin, K., Kekäläinen, J.: Cumulated Gain-Based Evaluation of IR Techniques. ACM Transactions on Information Systems (TOIS) 20(4), 422–446 (2002)

    CrossRef  Google Scholar 

  8. Savoy, J.: Why do Successful Search Systems Fail for Some Topics. In: Proc. 2007 ACM Symposium on Applied Computing (SAC 2007), pp. 872–877. ACM Press, New York (2007)

    Google Scholar 

  9. Voorhees, E.: Evaluation by Highly Relevant Documents. In: Proc. 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2001), pp. 74–82. ACM Press, New York (2001)

    CrossRef  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Angelini, M., Ferro, N., Santucci, G., Silvello, G. (2014). A Visual Interactive Environment for Making Sense of Experimental Data. In: , et al. Advances in Information Retrieval. ECIR 2014. Lecture Notes in Computer Science, vol 8416. Springer, Cham. https://doi.org/10.1007/978-3-319-06028-6_92

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-06028-6_92

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-06027-9

  • Online ISBN: 978-3-319-06028-6

  • eBook Packages: Computer ScienceComputer Science (R0)