The Semantic Framework of Library Intelligent Question Answering System Based on Exploratory Search Behavior

Analyze consultation question characteristics, identify users’ exploratory search behavior stage and library element demand, and integrate interview skills into intelligent question answering system, which improve the accuracy of library intelligent question answering. Analyze virtual consulting archives data of the National Library of China from 2011 to 2020, label characteristic vocabulary in users’ consultation questions, use SPSS software to test correlation between research elements, and design semantic framework of library intelligence question answering system based on hypothesis test results. Through data analysis, this research concludes that there is a relationship between library elements orientation in user consultation questions and cognitive stage, and target resources discovery plays a crucial role in users’ cognitive stage. Therefore, applying natural language processing technology to analyze user consultation questions, extracting characteristic vocabulary related to library elements, users’ cognitive stage and target resources, so as to generate personalized intelligent consultation answers. Accordingly, design a semantic framework for intelligent question answering system based on user exploratory search behavior, which will improve the answering accuracy of intelligent question answering system.