Towards fuzzy lexical reasoning: Proximity-based Logic Programming based on WordNet
What is it about?
Proximity-based Logic Programming is a formal framework for representing general or non-specialized knowledge. Although it is a powerful tool, it is too complex because the values of the proximity equations (fuzzy binary relations that establish the relationships among the symbols of a first-order language) must be manually defined by the designer of the system. In this paper, we propose a new framework for Proximity-based Logic Programming enhanced with WordNet and Interval-Valued Fuzzy Sets. Its main contribution is to compile automatically the information provided by WordNet and generate an interval-valued proximity relation on the set of their words. This proposal is completely integrated inside the unification mechanism of Bousi ~Prolog system. This allows us to introduce the lexical knowledge induced from a linguistic resource, such as WordNet, into an approximate reasoning system. To the best of our knowledge, this is the first time that WordNet is introduced into the core of a Prolog system by means of compilation techniques and lexical knowledge is combined with proximity-based unification frame
Why is it important?
This allows us to introduce the lexical knowledge induced from a linguistic resource, such as WordNet, into an approximate reasoning system.