An Intelligent Question Answering System of the Liao Dynasty Based on Knowledge Graph

Abstract

The Liao Dynasty was a minority regime established by the Khitan on the grasslands of northern China. To promote and spread the cultural knowledge of the Liao Dynasty, an intelligent question-and-answer system is constructed based on the knowledge graph in the historical and cultural field of the Liao Dynasty. In the traditional question answering system, the quality of answers was not high due to incomplete data and distinctive vocabulary. To solve this problem, a combination method of Liao Dynasty question-and-answer database and KB is proposed to realize knowledge graph question answering, and a joint model of Siamese LSTM and fusion MatchPyramid is proposed for semantic matching between questions in the question-and-answer database. With the joint model, it is easy to perform semantic matching by fusing sentence-level and word-level interactive features through LSTM and MatchPyramid. Furthermore, the question sentence with the same semantics as the user input question sentence is retrieved in the question-and-answer database, and the answer corresponding to the question sentence is returned as the result. The experimental results show that our proposed method has achieved relatively good performance in the historical domain of the Liao Dynasty and the open-domain knowledge graph, and improved the accuracy of question and answer.

Dynamic data‐driven railway bridge construction knowledge graph update method

“…Compared with traditional relational databases, KG enables more comprehensive and accurate data processing and analysis, better scalability and reusability, and more natural and flexible query and reasoning (Huang et al., 2022; Li et al., 2021). At present, KG has been widely applied in such fields as intelligent interaction (Liu et al., 2021; Tamašauskaitė & Groth, 2023; Zheng et al., 2021), financial risk control (Yang & Liao, 2022), medical health (Rotmensch et al., 2017), and urban intelligence (Ahmed et al., 2022). Some works integrating the knowledge resources in the enterprise based on the KG help to optimize the knowledge management of enterprise risk control, credit investigation, auditing, etc., and improve the intelligent level of enterprise management (Khan et al., 2016; Lai et al., 2023).…”

Construction and application of a knowledge graph-based question answering system for Nanjing Yunjin digital resources

“…To solve the issue of the same embedding for a word in different semantic contexts, some scholars have combined BiLSTM with CRF to acquire bidirectional semantic information [28]. For instance, Liu et al constructed a KG and Q&A system in the field of Liao Dynasty history and culture based on the BiLSTM-CRF model [29]. Many researchers improved this model.…”