Hypergraphs in Logic Programming

Heterogeneous data is a significant topic in today’s context, necessitating the development of AI tools. Logic programming is a powerful approach for extracting information from datasets, enabling the interpretation of natural language as logical rules. This paper introduces a novel representation of logic normal programs, which include negated variables, using labeled hypergraphs. This representation provides a comprehensive characterization of the program, capturing all available information and relationships among variables in a specific hypergraph. Such characterization is highly advantageous, particularly for computing program consequences and models through hypergraph theory.