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A Template-based Information Extraction System for Text Understanding
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 182 - Number 28 |
| Year of Publication: 2018 |
| Authors: Dania Sagheer, Fadel Sukkar |
10.5120/ijca2018918167
|
Dania Sagheer, Fadel Sukkar . A Template-based Information Extraction System for Text Understanding. International Journal of Computer Applications. 182, 28 ( Nov 2018), 28-33. DOI=10.5120/ijca2018918167
Abstract
This paper presents a template-based information extraction system for Arabic descriptive text understanding. The system depends on knowledge base. The knowledge base contains facts and rules. The facts are derived from AL Khalil lexicon, Al Ramous lexicon and a Stanford model. The rules represent the designed templates. The templates are helpful for detecting the meaning of the text. the inference engine depends on the hybrid chaining to fill the slots in templates from the text. The semantic criterion is augmented to the templates. the criterion calculates the frequency of the template in the text. the system is tested on Arabic texts taken in oil production domain from Arabic news website as Arabic CNN, and Arabic BBC. The system implements good response in getting the goal of descriptive text. Text understanding is made efficiency, and high accuracy is obtained.
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