Probabilistic models in information retrieval
The Computer Journal - Special issue on information retrieval
Some inconsistencies and misidentified modeling assumptions in probabilistic information retrieval
ACM Transactions on Information Systems (TOIS)
A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
A hidden Markov model information retrieval system
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Information retrieval as statistical translation
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
A general language model for information retrieval (poster abstract)
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Precision Weighting—An Effective Automatic Indexing Method
Journal of the ACM (JACM)
A probabilistic model of information retrieval: development and comparative experiments
Information Processing and Management: an International Journal
Relevance based language models
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
The unified probabilistic model for IR
SIGIR '82 Proceedings of the 5th annual ACM conference on Research and development in information retrieval
Language Modeling for Information Retrieval
Language Modeling for Information Retrieval
A study of smoothing methods for language models applied to information retrieval
ACM Transactions on Information Systems (TOIS)
Dependence language model for information retrieval
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
On Event Spaces and Probabilistic Models in Information Retrieval
Information Retrieval
A risk minimization framework for information retrieval
Information Processing and Management: an International Journal - Special issue: Formal methods for information retrieval
A parallel derivation of probabilistic information retrieval models
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Probability ranking principle via optimal expected rank
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
A probability ranking principle for interactive information retrieval
Information Retrieval
Interpreting TF-IDF term weights as making relevance decisions
ACM Transactions on Information Systems (TOIS)
ICTIR '09 Proceedings of the 2nd International Conference on Theory of Information Retrieval: Advances in Information Retrieval Theory
Building a framework for the probability ranking principle by a family of expected weighted rank
ACM Transactions on Information Systems (TOIS)
A Generative Theory of Relevance
Journal of the American Society for Information Science and Technology
Towards a better understanding of the relationship between probabilistic models in IR
ICTIR'11 Proceedings of the Third international conference on Advances in information retrieval theory
IR models: foundations and relationships
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
More Than Words: A Review of Planets, Stars and Sample Spaces
Proceedings of the 2013 Conference on the Theory of Information Retrieval
IR Models: Foundations and Relationships
Proceedings of the 2013 Conference on the Theory of Information Retrieval
Probabilistic models in IR and their relationships
Information Retrieval
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This paper discusses various issues about the rank equivalence of Lafferty and Zhai between the log-odds ratio and the query likelihood of probabilistic retrieval models. It highlights that Robertson's concerns about this equivalence may arise when multiple probability distributions are assumed to be uniformly distributed, after assuming that the marginal probability logically follows from Kolmogorov's probability axioms. It also clarifies that there are two types of rank equivalence relations between probabilistic models, namely strict and weak rank equivalence. This paper focuses on the strict rank equivalence which requires the event spaces of the participating probabilistic models to be identical. It is possible that two probabilistic models are strict rank equivalent when they use different probability estimation methods. This paper shows that the query likelihood, p(q|d, r), is strict rank equivalent to p(q|d) of the language model of Ponte and Croft by applying assumptions 1 and 2 of Lafferty and Zhai. In addition, some statistical component language model may be strict rank equivalent to the log-odds ratio, and that some statistical component model using the log-odds ratio may be strict rank equivalent to the query likelihood. Finally, we suggest adding a random variable for the user information need to the probabilistic retrieval models for clarification when these models deal with multiple requests.