Skip to main content

An Analysis of Ranking Principles and Retrieval Strategies

  • Conference paper
Advances in Information Retrieval Theory (ICTIR 2011)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6931))

Included in the following conference series:

Abstract

The assumptions underlying the Probability Ranking Principle (PRP) have led to a number of alternative approaches that cater or compensate for the PRP’s limitations. All alternatives deviate from the PRP by incorporating dependencies. This results in a re-ranking that promotes or demotes documents depending upon their relationship with the documents that have been already ranked. In this paper, we compare and contrast the behaviour of state-of-the-art ranking strategies and principles. To do so, we tease out analytical relationships between the ranking approaches and we investigate the document kinematics to visualise the effects of the different approaches on document ranking.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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. Carbonell, J., Goldstein, J.: The use of MMR, diversity-based reranking for reordering documents and producing summaries. In: SIGIR 1998, pp. 335–336 (1998)

    Google Scholar 

  2. Chen, H., Karger, D.R.: Less is more: probabilistic models for retrieving fewer relevant documents. In: SIGIR 2006, pp. 429–436 (2006)

    Google Scholar 

  3. Fuhr, N.: A probability ranking principle for iir. JIR 12(3), 251–265 (2008)

    Google Scholar 

  4. Goffman, W.: On relevance as a measure. Info. Stor. & Ret. 2(3), 201–203 (1964)

    Article  MathSciNet  Google Scholar 

  5. Gordon, M.D., Lenk, P.: When is the prp suboptimal. JASIS 43(1), 1–14 (1999)

    Article  Google Scholar 

  6. Robertson, S.E.: The probability ranking principle in IR. J. Doc. 33, 294–304 (1977)

    Article  Google Scholar 

  7. Wang, J., Zhu, J.: Portfolio theory of information retrieval. In: SIGIR 2009, pp. 115–122 (2009)

    Google Scholar 

  8. Zuccon, G., Azzopardi, L.: Using the quantum probability ranking principle to rank interdependent documents. In: Gurrin, C., He, Y., Kazai, G., Kruschwitz, U., Little, S., Roelleke, T., Rüger, S., van Rijsbergen, K. (eds.) ECIR 2010. LNCS, vol. 5993, pp. 357–369. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  9. Zuccon, G., Azzopardi, L., Hauff, C., van Rijsbergen, C.J.: Estimating interference in the QPRP for subtopic retrieval. In: SIGIR 2010, pp. 741–742 (2010)

    Google Scholar 

  10. Zuccon, G., Azzopardi, L., van Rijsbergen, C.J.: The interactive PRP for diversifying document rankings. In: SIGIR (to appear, 2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Zuccon, G., Azzopardi, L., Van Rijsbergen, C.J.K. (2011). An Analysis of Ranking Principles and Retrieval Strategies. In: Amati, G., Crestani, F. (eds) Advances in Information Retrieval Theory. ICTIR 2011. Lecture Notes in Computer Science, vol 6931. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23318-0_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-23318-0_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23317-3

  • Online ISBN: 978-3-642-23318-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics