Querying databases containing multivalued attributes using veristic variables
Fuzzy Sets and Systems - Data bases and approximate reasoning
Fuzzy logic methods in recommender systems
Fuzzy Sets and Systems - Theme: Multicriteria decision
Entropy conserving probability transforms and the entailment principle
Fuzzy Sets and Systems
A Reasoning Methodology for CW-Based Question Answering Systems
WILF '09 Proceedings of the 8th International Workshop on Fuzzy Logic and Applications
Representing uncertainty on set-valued variables using belief functions
Artificial Intelligence
Hi-index | 0.00 |
We distinguish between variables having only one solution (possibilistic) and those allowing multiple solutions (veristic). A representation of information contained in statements involving veristic variables is presented. Using this representation we begin to develop a structure for the manipulation of knowledge involving variables that can have multiple solutions. The verity distribution is introduced to capture information about these variables. We show how to combine information involving veristic variables. We study qualified and quantified statements as well as the entailment and extension principles in this framework