The DOI matches its Crossref record.
THE PROBABILITY RANKING PRINCIPLE IN IR
Abstract
The principle that, for optimal retrieval, documents should be ranked in order of the probability of relevance or usefulness has been brought into question by Cooper. It is shown that the principle can be justified under certain assumptions, but that in cases where these assumptions do not hold, the principle is not valid. The major problem appears to lie in the way the principle considers each document independently of the rest. The nature of the information on the basis of which the system decides whether or not to retrieve the documents determines whether the document‐by‐document approach is valid.
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IR's foundational work provided explicit accounts of relevance and retrieval models derived from them, giving later researchers clear assumptions to test and extend.
“Its foundational work provided explicit accounts of relevance and retrieval models derived from them [45, 48, 49, 51], giving later researchers clear assumptions to test and extend.”
From Agentic Memory Management Is the Next Frontier of Information Retrieval (2026) · cites this paper as [49]
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Research works printed but not linked: 11
- 10.1145/321033.321035 · DOI
- ROBERTSON S. E., 1971, Information Processing and Management, 13, 247151
- ROBERTSON, S. E. A theoretical model of the retrieval characteristics of information retrieval systems. Ph.D. thesis,University of London, 1976.
- 10.1002/asi.4630240204 · DOI
- 10.1002/asi.5090190108 · DOI
- 10.1002/asi.4630270302 · DOI
- KEEN E. M., 1972, Report of an information science index languages test
- 10.1108/eb026557 · DOI
- STIRLING K. H, 1975, Proceedings of the American Societyfor Information Science, 12, 105
- 10.1016/0020-0271(68)90030-2 · DOI
- 10.1016/0306-4573(76)90051-0 · DOI
Cited by
Sorted by citations
The probabilistic relevance framework: BM25 and beyond
Robertson, S., & Zaragoza, H. (2009) · Foundations and Trends® in Information Retrieval · doi:10.1561/1500000019 · Cited by 3,374
Self-citationPubMed related articles: a probabilistic topic-based model for content similarity
Lin, J., & Wilbur, W. J. (2007) · BMC Bioinformatics · doi:10.1186/1471-2105-8-423 · Cited by 243
Evolution and impact of bias in human and machine learning algorithm interaction
Sun, W., Nasraoui, O., & Shafto, P. (2020) · PLOS ONE · doi:10.1371/journal.pone.0235502 · Cited by 116
“For instance, in the probabilistic retrieval model, optimal retrieval is obtained when search results are ranked according to their relevance probabilities [2].”
BackgroundInfluentialRetrieval-Augmented Generation (RAG)
Klesel, M., & Wittmann, H. F. (2025) · Business & Information Systems Engineering · doi:10.1007/s12599-025-00945-3 · Cited by 92
“Most commonly, the ranking system is built upon the probability ranking principle (Robertson 1977), which is not always ideal.”
Beyond Ranking: Optimizing Whole-Page Presentation
Wang, Y., Yin, D., Jie, L., Wang, P., Yamada, M., Chang, Y., & Mei, Q. (2016) · Proceedings of the Ninth ACM International Conference on Web Search and Data Mining · doi:10.1145/2835776.2835824 · Cited by 66
Metadata
- Authors
- ROBERTSON, S. E.
- Affiliations
- University College London (GB)
- Corresponding author
- ROBERTSON, S.E.
- ORCID
- ROBERTSON, S.E.
- Venue
- Journal of Documentation
- Publisher
- Emerald
- Published
- 1977-04-01
- Volume
- 33
- Issue
- 4
- Pages
- 294-304
- ISSN
- 0022-0418 (ISSN-L)
- OpenAlex
- W2048045485
- Cited by
- 1,103
- References
- 0
- Citations by year
- 2026: 14 · 2025: 26 · 2024: 40 · 2023: 20 · 2022: 31 · 2021: 45 · 2020: 79 · 2019: 27 · 2018: 21 · 2017: 29 · 2016: 56 · 2015: 37 · 2014: 39 · 2013: 43 · 2012: 53
- FWCI
- 3.77
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Documentation (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
- Physical Sciences › Mathematics › Theoretical Computer Science › Algorithms and Data Compression
- Physical Sciences › Computer Science › Artificial Intelligence › Advanced Text Analysis Techniques
- Keywords
- probability ranking principle, information retrieval, document ranking, relevance, retrieval effectiveness
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