An Automated Approach For Relation Extraction In Text Data Using Context Free Grammars
With the growing demand for text data mining in order to accomplish relation between multiple text entities in
order to extract high level information, it is mandatory to frame an automated algorithm based on grammatical inferences.
Todays’ business, social media and including education industry generates huge amount of data from multiple transactions
inside and outside, educators and online teaching leaning operations and social connections like Facebook, Twitter and other.
Hence a use of supervised learning methods should be an additional factor to infer context free grammar from the text that
connects multiple termed entities. The approach focuses on generalization of grammar from the text using minimal
descriptive length. The final results will demonstrate that the automated algorithm performs high precision generalization.
Keywords — CFG, Text Mining, Relation Extraction, Comparative Analysis.