Abstract
In this paper, we have proposed a framework to support the semantic question answering over the RDF data cube that is published according to the Linked Open Data (LOD) principles. As statistical data published all over the Internet there is a need to empowers the non-experts to query in the form of the natural language. But, the existing question answering system unable to support query on the statistical data in the form of the RDF cube. The current research is motivated by the need of the clinical organizations, who wish to develop a platform for analyzing the clinical data across multiple clinical sites. Linked open data (LOD) provides a support to published statistical data in the form of the RDF cube. Our proposed framework will provide a support to interact in the form of the natural language question answering that will produce the SPARQL query to extract the answer from the RDF data cube. In future, we will develop the benchmark to calculate the accuracy of the answer.
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Acknowledgments
This work was supported by the Industrial Core Technology Development Program (10049079), Develop of mining core technology exploiting personal big data) funded by the Ministry of Trade, Industry and Energy (MOTIE, Korea).
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Akhtar, U., Hussain, J., Lee, S. (2017). Medical Semantic Question Answering Framework on RDF Data Cubes. In: Mokhtari, M., Abdulrazak, B., Aloulou, H. (eds) Enhanced Quality of Life and Smart Living. ICOST 2017. Lecture Notes in Computer Science(), vol 10461. Springer, Cham. https://doi.org/10.1007/978-3-319-66188-9_23
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DOI: https://doi.org/10.1007/978-3-319-66188-9_23
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