Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Handbook of logic in artificial intelligence and logic programming (vol. 3)
Introduction to Bayesian Networks
Introduction to Bayesian Networks
Syntactic Combination of Uncertain Information: A Possibilistic Approach
ECSQARU/FAPR '97 Proceedings of the First International Joint Conference on Qualitative and Quantitative Practical Reasoning
Background and Perspectives of Possibilistic Graphical Models
ECSQARU/FAPR '97 Proceedings of the First International Joint Conference on Qualitative and Quantitative Practical Reasoning
The Possibilistic Handling of Irrelevance in Exception-Tolerant Reasoning
Annals of Mathematics and Artificial Intelligence
A theoretical framework for possibilistic independence in a weakly ordered setting
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Anytime Possibilistic Propagation Algorithm
Soft-Ware 2002 Proceedings of the First International Conference on Computing in an Imperfect World
Confidence Relations as a Basis for Uncertainty Modeling, Plausible Reasoning, and Belief Revision
AI '01 Proceedings of the 14th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Bridging Logical, Comparative, and Graphical Possibilistic Representation Frameworks
ECSQARU '01 Proceedings of the 6th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Possibility and necessity measures for relevance assessment
Proceedings of the ACM first Ph.D. workshop in CIKM
An Efficient Algorithm for Naive Possibilistic Classifiers with Uncertain Inputs
SUM '08 Proceedings of the 2nd international conference on Scalable Uncertainty Management
Toward a computer study of the reliability of Arabic stories
Journal of the American Society for Information Science and Technology
Graphical readings of possibilistic logic bases
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
A model for information retrieval based on possibilistic networks
SPIRE'05 Proceedings of the 12th international conference on String Processing and Information Retrieval
Possibilistic model for aggregated search in XML documents
International Journal of Intelligent Information and Database Systems
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Possibilistic logic bases and possibilistic graphs are two different frameworks of interest for representing knowledge. The former stratifies the pieces of knowledge (expressed by logical formulas) according to their level of certainty, while the latter exhibits relationships between variables. The two types of representations are semantically equivalent when they lead to the same possibility distribution (which rankorders the possible interpretations). A possibility distribution can be decomposed using a chain rule which may be based on two different kinds of conditioning which exist in possibility theory (one based on product in a numerical setting, one based on minimum operation in a qualitative setting). These two types of conditioning induce two kinds of possibilistic graphs. In both cases, a translation of these graphs into possibilistic bases is provided. The converse translation from a possibilistic knowledge base into a min-based graph is also described