Rule Mining from Raw Text

EasyChair Preprint 6635

Abstract

Expert systems require knowledge for their work. Rule-based expert systems require rules that is one of the knowledge type. It is possible to generate rules from raw ontologies, however ontologies are not very widespread in the Web at this time. The solution may be to generate ontology from raw text and then to generate rules from the ontology. Thus, ontology generation is an intermediate link, but the presence of an intermediate link always increases the difficulty and decreases efficiency everywhere. It is necessary to find the way of knowledge extraction from raw text. This paper shows how knowledge in the form of rules can be mined from raw text.

Keyphrases: Natural Language Processing, expert systems, rules

@booklet{EasyChair:6635,
  author    = {Olegs Verhodubs},
  title     = {Rule Mining from Raw Text},
  howpublished = {EasyChair Preprint 6635},
  year      = {EasyChair, 2021}}