Research on Question Classification Model of Question Answering System Oriented WarGaming
SUN Zejian
SI Guangya
LIU Yang
Abstract：By analyzing the common problems in the process of war gaming,a question classification model is designed for a QA(question answering)system oriented a specific situation. The question classification model generates word vectors by word2vec based on statistical methods,and generates word weight by TextRank algorithm so as to complete the question representation. The classification combines two different models of question similarity calculation through the improved KNN(K Nearest Neighbor)algo?rithm,balancing the computation complexity and accuracy. The WMD(Word Move Distance)algorithm is based on the word vector to calculate the similarity of questions more accurate algorithm,which also has the disadvantage of high algorithm complexity howev?er. In this paper,the improved KNN algorithm is combined with the traditional algorithm,in order to complete the required question classification task better.
Keywords：Word2vecWMD algorithmwargamingQA Systemquestion classification
Publication Date：2019-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 308-313,319 )