A Rule-based Inference Method for Natural Language Propositions Involving Fuzzy Quantifiers and Truth Qualifiers

Fuzzy Quantifiers: A Natural Language Technique for Data Fusion

Fuzzy quantifiers like ‘almost all’ and ‘about half’ abound in natural language. They are used for describing uncertain facts, quantitative relations and processes. An implementation of these quantifiers can provide expressive and easy-to-use operators for aggregation and data fusion, but also for steering the fusion process on a higher level through a safe transfer of expert-knowledge expresse...

Fuzzy quantifiers in natural language:: semantics and computational models

Principle-Based Interpretation of Natural Language Quantifiers

This paper describes a working prototype that determines possible relative quantifier scopes and pronoun bindings for natural language sentences, with coverage of a variety of problematic cases. The prototype parses a significant fragment of English, positing empty categories and deriving various relationships among constituents in addition to dominance. It applies cross-linguistically valid pr...

Fuzzy reasoning models and fuzzy truth value based inference

Patterns of fuzzy rule-based inference

Processing information in fuzzy rule-based systems generally employs one of two patterns of inference: composition or compatibility modification. Composition originated as a generalization of binary logical deduction to fuzzy logic, while compatibility modification was developed to facilitate the evaluation of rules by separating the evaluation of the input from the generation of the output. Th...