A Noval Deep Learning Approach For Semantic Information Extraction From Medicinal Crops
European Journal of Molecular & Clinical Medicine,
2020, Volume 7, Issue 8, Pages 1363-1378
Abstract
To extract significant information from large amount of data is an essential task of natural language processing. Every Information Extraction technique design different rules for tuning the domain based raw data to extract semantic information. Huge amount of unstructured data in agricultural domain increases the complexity of information extraction techniques. The paper presented an algorithm of semantic information extraction from a text article on health benefits from medicinal plants. The proposed algorithm apply deep leaning techniques to extract semantic (relational) information from medicinal crops corpus. The proposed algorithm tuned and tested on agricultural and weather data collected from DACFW, Government of India. The experimental results stated that the proposed deep learning based method achieved nearly 95% prediction accuracy. Proposed method also compared with existing techniques like Self-Organizing Map (SOM) and Ensemble Neural Network (ENN).
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