@article{MAKHILLJEAS2019142218639,
    title = {An Efficient Semantic Analysis Technique for the Question Answering Systems},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {14},
    number = {22},
    pages = {8289-8292},
    year = {2019},
    issn = {1816-949x},
    doi = {jeasci.2019.8289.8292},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2019.8289.8292},
    author = {Ibrahim and},
    keywords = {conceptual graphs,semantic
search,keywords search,concepts extraction,question answering systems,Information retrieval},
    abstract = {Question Answering (QA) systems provide a natural way of requesting specific and concise
information from a given data source. A crucial stage of such a system is the information retrieval stage which
retrieves the possible passages based on their relevance to the question. Accordingly, this study introduces
an approach of knowledge extraction of information retrieval from these corpus based on Conceptual Graph
(CG). This study discusses how to enhance the accuracy of text-based QA system by modeling the knowledge
automatically by using CGF and answers question semantically. The proposed approach showed efficient
results of information retrieval measurement through compare recall and precision with another traditional
method that has been applied in this same test collection. The result of experiments produced a score of 0.919
for precision and 0.853 for recall. We evaluate our model and show that for the answering task it performs better
than standard QA Model.}
    }