A note on rule representation in expert systems
Information Sciences: an International Journal
On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
Connectives and quantifiers in fuzzy sets
Fuzzy Sets and Systems - Special memorial volume on foundations of fuzzy reasoning
Fuzzy Sets and Systems
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Cardinality, quantifiers, and the aggregation of fuzzy criteria
Fuzzy Sets and Systems - Special issue on fuzzy information processing
An overview of fuzzy quantifiers. (I). Interpretations
Fuzzy Sets and Systems
Information combination operators for data fusion: a comparative review with classification
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Experiments on using fuzzy quantified sentences in adhoc retrieval
Proceedings of the 2004 ACM symposium on Applied computing
Linguistic quantifiers modeled by Sugeno integrals
Artificial Intelligence
Spanish Temporal Expressions: Some Forms Reinforced by an Adverb
MICAI '08 Proceedings of the 7th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Linguistic quantifiers modeled by Sugeno integrals
Artificial Intelligence
Modelling fuzzy quantified statements under a voting model interpretation of fuzzy sets
IFSA'03 Proceedings of the 10th international fuzzy systems association World Congress conference on Fuzzy sets and systems
News generating via fuzzy summarization of databases
SOFSEM'06 Proceedings of the 32nd conference on Current Trends in Theory and Practice of Computer Science
Hi-index | 0.00 |
Fuzzy quantification is a linguistic granulation technique capable of expressing the global characteristics of a collection of individuals, or a relation between individuals, through meaningful linguistic summaries. However, existing approaches to fuzzy quantification fail to provide convincing results in the important case of two-place quantification (e.g. "many blondes are tall"). We develop an axiomatic framework for fuzzy quantification which complies with a large number of linguistically motivated adequacy criteria. In particular, we present the first models of fuzzy quantification which provide an adequate account of the "hard" cases of multiplace quantifiers, non-monotonic quantifiers, and non-quantitative quantifiers, and we show how the resuiting operators can be efficiently implemented based on histogram computations.