Using the quantum probability ranking principle to rank interdependent documents

Zuccon, Guido & Azzopardi, Leif (2010) Using the quantum probability ranking principle to rank interdependent documents. In Lecture Notes in Computer Science : Advances in Information Retrieval, Springer Berlin Heidelberg, Milton Keynes, UK, pp. 357-369.

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A known limitation of the Probability Ranking Principle (PRP) is that it does not cater for dependence between documents. Recently, the Quantum Probability Ranking Principle (QPRP) has been proposed, which implicitly captures dependencies between documents through “quantum interference”. This paper explores whether this new ranking principle leads to improved performance for subtopic retrieval, where novelty and diversity is required. In a thorough empirical investigation, models based on the PRP, as well as other recently proposed ranking strategies for subtopic retrieval (i.e. Maximal Marginal Relevance (MMR) and Portfolio Theory(PT)), are compared against the QPRP. On the given task, it is shown that the QPRP outperforms these other ranking strategies. And unlike MMR and PT, one of the main advantages of the QPRP is that no parameter estimation/tuning is required; making the QPRP both simple and effective. This research demonstrates that the application of quantum theory to problems within information retrieval can lead to significant improvements.

Impact and interest:

14 citations in Scopus
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25 citations in Web of Science®

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ID Code: 69261
Item Type: Conference Paper
Refereed: No
Additional Information: 32nd European Conference on IR Research, ECIR 2010, Milton Keynes, UK, March 28-31, 2010.Proceedings
DOI: 10.1007/978-3-642-12275-0_32
ISBN: 9783642122750
ISSN: 0302-9743
Divisions: Current > Institutes > Institute for Future Environments
Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2010 Springer-Verlag Berlin Heidelberg
Copyright Statement: The final publication is available at Springer via
Deposited On: 02 Jun 2014 02:45
Last Modified: 16 Jul 2014 06:44

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