Fuzzy Datalog with background knowledge

From Fuzzy Datalog to Multivalued Knowledge-Base

Human knowledge consists of static and dynamic knowledge chunks. The static ones include the so called lexical knowledge or the ability to sense similarities between facts and between predicates. Through dynamic attainments one can make deductions or one can give answers to a question. There are several and very different approaches to make a model of human knowledge, but one of the most common...

Attribute Exploration with Fuzzy Attributes and Background Knowledge

Attribute exploration is a formal concept analytical tool for knowledge discovery by interactive determination of the implications holding between a given set of attributes. The corresponding algorithm queries the user in an efficient way about the implications between the attributes. The result of the exploration process is a representative set of examples for the entire theory and a set of im...

From Fuzzy - to Bipolar - Datalog

Abstract. In this work we present several possible extensions of fuzzy Datalog. At first the concept of fuzzy Datalog will be summarized, then its extension for intuitionisticand interval-valued fuzzy logic is given and the concept of bipolar fuzzy Datalog is introduced.

Background Knowledge and Translation Ability

Attribute Exploration with Background Knowledge