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Building a Knowledge Base Shell Based on Exploring Text Semantic Relations from Arabic Text

This research aims at focusing on building a knowledge base shell which task is to automatically build the knowledge base component from text sources. The proposed research aims at considering the Arabic text sources as one of the main challenges in due to the difficulty in processing Arabic text that suffers from the high inflection, shortcuts, and the varieties in letters’ representation. The research restored the confidence in the term frequency method and the research adopts the semantic relations network representation. The research applied the experiment for building the weeds’ identification facts’ part in the knowledge-based system. The experiment applied the proposed framework on two sources, the precision, recall, and f-score have been measured which resulted in an average of 91.2%, 91.1%, and 91% respectively. The evaluation metrics provide a promising perspective in the proposed approach with more focus on the bottlenecks for enhancements.