Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Inference networks for document retrieval
SIGIR '90 Proceedings of the 13th annual international ACM SIGIR conference on Research and development in information retrieval
Inference networks for document retrieval
Inference networks for document retrieval
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Relevance feedback and inference networks
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Applying Bayesian networks to information retrieval
Communications of the ACM
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
On Relevance, Probabilistic Indexing and Information Retrieval
Journal of the ACM (JACM)
Link-based and content-based evidential information in a belief network model
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
A probabilistic model of information retrieval: development and comparative experiments
Information Processing and Management: an International Journal
A probabilistic model of information retrieval: development and comparative experiments Part 2
Information Processing and Management: an International Journal
Introduction to Bayesian Networks
Introduction to Bayesian Networks
A Layered Bayesian Network Model for Document Retrieval
Proceedings of the 24th BCS-IRSG European Colloquium on IR Research: Advances in Information Retrieval
Building Bayesian Network-Based Information Retrieval Systems
DEXA '00 Proceedings of the 11th International Workshop on Database and Expert Systems Applications
Query expansion in information retrieval systems using a Bayesian network-based thesaurus
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Bayesian networks and information retrieval: an introduction to the special issue
Information Processing and Management: an International Journal - Special issue: Bayesian networks and information retrieval
A model for information retrieval based on possibilistic networks
SPIRE'05 Proceedings of the 12th international conference on String Processing and Information Retrieval
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Relevance Feedback consists in automatically formulating a new query according to the relevance judgments provided by the user after evaluating a set of retrieved documents. In this article, we introduce several relevance feedback methods for the Bayesian Network Retrieval Model. The theoretical frame on which our methods are based uses the concept of partial evidences, which summarize the new pieces of information gathered after evaluating the results obtained by the original query. These partial evidences are inserted into the underlying Bayesian network and a new inference process (probabilities propagation) is run to compute the posterior relevance probabilities of the documents in the collection given the new query. The quality of the proposed methods is tested using a preliminary experimentation with different standard document collections.