Information Retrieval

, Volume 3, Issue 3, pp 217–227 | Cite as

The Probability Ranking Principle Revisited

  • Martin Wechsler
  • Peter Schäuble


A theoretic framework for multimedia information retrieval is introduced which guarantees optimal retrieval effectiveness. In particular, a Ranking Principle for Distributed Multimedia-Documents (RPDM) is described together with an algorithm that satisfies this principle. Finally, the RPDM is shown to be a generalization of the Probability Ranking principle (PRP) which guarantees optimal retrieval effectiveness in the case of text document retrieval. The PRP justifies theoretically the relevance ranking adopted by modern search engines. In contrast to the classical PRP, the new RPDM takes into account transmission and inspection time, and most importantly, aspectual recall rather than simple recall.

multimedia information retrieval probability ranking principle relevance ranking optimal search performance maximum retrieval effectiveness 


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  1. Domschke W and Drexl A (1991) Einf¨uhrung in Operations Research. Springer, Berlin.Google Scholar
  2. Kreher D and Stinson D (1998) Combinatorial Algorithms: Generation, Enumeration and Search. CRC Press, Boca Raton.Google Scholar
  3. Lu G (1996) Communication and Computing for Distributed Multimedia Systems. Artech House, Boston.Google Scholar
  4. Mitchell M (1996) An Introduction to Genetic Algorithms. The MIT Press, Cambridge.Google Scholar
  5. Nievergelt J (1977) Combinatorial Algorithms. Prentice Hall, Englewood Cliffs.Google Scholar
  6. Pan D (1995) A tutorial on MPEG/audio compression. IEEE Multimedia, 2(2):60-74.Google Scholar
  7. Robertson SE (1977) The probability ranking principle in IR. Journal of Documentation, 33(4):294-304.Google Scholar
  8. Schäuble P (1997) Multimedia Information Retrieval-Content-Based Information Retrieval from Large Text and Audio Databases. Kluwer Academic Publishers, Boston.Google Scholar
  9. Sutcliffe A, Hare M, Doubleday A and Ryan M (1997). Empirical studies in multimedia information retrieval. Intelligent Multimedia Information Retrieval, AAAI Press, pp. 449-472.Google Scholar
  10. Vidal R (1993) Applied Simulated Annealing. Springer, Berlin.Google Scholar
  11. Voorhees E and Harman D (1999) Overview of the seventh text retrieval conference (TREC-7). In: TREC-7 Proceedings.Google Scholar
  12. Wechsler M and Schäuble P (1999).A Newranking principle for multimedia information retrieval. In: Proceedings of the Fourth ACM Conference on Digital Libraries.Google Scholar
  13. Wechsler M (1998) Spoken document retrieval based on phoneme recognition. PhD Thesis, ETH Zurich. Diss. No. 12879.Google Scholar

Copyright information

© Kluwer Academic Publishers 2000

Authors and Affiliations

  • Martin Wechsler
    • 1
  • Peter Schäuble
    • 2
  1. 1.McKinsey & CompanySwitzerland
  2. 2.Eurospider Information Technology AGZürichSwitzerland

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