Linguistic Approach to Semantic Correlation Rules

As communication between humans and machines in natural language still seems essential, especially for end users, Natural Language Processing (NLP) methods are used to classify interpret this. NLP, as a technology, combines grammatical, semantical, pragmatical analyses with statistics or machine learning make logically understandable by allow new interpretations of data contrast predefined logical structures. Some NLP do not go far beyond retrieving the indexation content. Therefore, is considered very simple linguistic approach. Semantic correlation rules offer possibility retrieve easy semantic relations without special tool using set rules. this paper aims examine, which extend Correlation Rules (SCRs) will be able what method can up further interpretation data. In order so, an model was modelled that enriched semantical give more context. These were then queried SCRs method.