Conceptual Graphs and Fuzzy Logic, 2010 A Fusion for Representing and Reasoning with Linguistic Information Studies in Computational Intelligence Series, Vol. 306

In this volume, first we formulate a framework of fuzzy types to represent both partial truth and uncertainty about concept and relation types in conceptual graphs. Like fuzzy attribute values, fuzzy types also form a lattice laying a common ground for lattice-based computation of fuzzy granules. Second, for automated reasoning with fuzzy conceptual graphs, we develop foundations of order-sorted fuzzy set logic programming, extending the theory of annotated logic programs of Kifer and Subrahmanian (1992). Third, we show some recent applications of fuzzy conceptual graphs to modelling and computing with generally quantified statements, approximate knowledge retrieval, and natural language query understanding.

Fuzzy Conceptual Graphs.- Annotated Fuzzy Logic Programming.- Fuzzy Conceptual Graph Programming.- Modelling and Computing with Generally Quantified Statements.- Approximate Knowledge Retrieval.- Natural Language Query Understanding.

Fusing conceptual graphs and fuzzy logic into a formalism for computing with words; fusing conceptual graphs and fuzzy logic into a formalism for computing with words State-of-the-Art book Written by leading experts