Abstract
This paper presents an ongoing study of the structure and operation of a dynamic question answering system. The main result of this paper is to use architecture to master more intelligent answers. This system is designed for the natural language process in the open domain of knowledge base of HowNet on the basis of knowledge base. Natural language processing can get better results. At the same time, the system has the ability of learning through the update of database. The purpose of this system is to improve the search speed and search the answers accurately. This paper improves the algorithm from three aspects. In text clustering, the new ant tree algorithm is used to replace the original k-means algorithm to accelerate the clustering. When decomposing keywords, we combine classic algorithm and knowledge base of HowNet to understand natural language with high precision. When we do the answer extraction, we should consider the necessary factors to improve the old algorithm. By testing the prototype of the dynamic question answering system, the improved algorithm is proved to be effective.
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Jiang, J., Wang, J., Wang, D., Song, X. (2020). Algorithm Design of Dynamic Question Answering System Based on Knowledge Base. In: Xu, Z., Parizi, R., Hammoudeh, M., Loyola-González, O. (eds) Cyber Security Intelligence and Analytics. CSIA 2020. Advances in Intelligent Systems and Computing, vol 1146. Springer, Cham. https://doi.org/10.1007/978-3-030-43306-2_43
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DOI: https://doi.org/10.1007/978-3-030-43306-2_43
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