Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Inference networks for document retrieval
SIGIR '90 Proceedings of the 13th annual international ACM SIGIR conference on Research and development in information retrieval
Retrieving information by fuzzification of queries
Journal of Intelligent Information Systems - Special issue: fuzzy logic and uncertainty management in information systems
Some simple effective approximations to the 2-Poisson model for probabilistic weighted retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Automatic Indexing: An Experimental Inquiry
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 Part 2
Information Processing and Management: an International Journal
Bayesian Networks and Decision Graphs
Bayesian Networks and Decision Graphs
Implementing relevance feedback in the Bayesian network retrieval model
Journal of the American Society for Information Science and Technology - Mathematical, logical, and formal methods in information retrieval
The SMART Retrieval System—Experiments in Automatic Document Processing
The SMART Retrieval System—Experiments in Automatic Document Processing
The automatic creation of literature abstracts
IBM Journal of Research and Development
Possibilistic logic bases and possibilistic graphs
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Possibility and necessity measures for relevance assessment
Proceedings of the ACM first Ph.D. workshop in CIKM
Vagueness and uncertainty in information retrieval: how can fuzzy sets help?
Proceedings of the 2006 international workshop on Research issues in digital libraries
Graded-Inclusion-Based Information Retrieval Systems
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Fuzzy information retrieval model revisited
Fuzzy Sets and Systems
Possibilistic networks for information retrieval
International Journal of Approximate Reasoning
Possibilistic model for aggregated search in XML documents
International Journal of Intelligent Information and Database Systems
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This paper proposes a model for Information Retrieval (IR) based on possibilistic directed networks. Relations documents-terms and query-terms are modeled through possibility and necessity measures rather than a probability measure. The relevance value for the document given the query is measured by two degrees: the necessity and the possibility. More precisely, the user's query triggers a propagation process to retrieve necessarily or at least possibly relevant documents. The possibility degree is convenient to filter documents out from the response (retrieved documents) and the necessity degree is useful for document relevance confirmation. Separating these notions may account for the imprecision pervading the retrieval process. Moreover, an improved weighting of terms in a query not present in the document is introduced. Experiments carried out on a sub-collection of CLEF, namely LeMonde 1994, a French newspapers collection, showed the effectiveness of the model.