Research on Construction of Chinese Technology Literature Question Answering System Based on Knowledge Graph
Article No.: 34, Pages 1 - 5
Abstract
In order to improve the knowledge service ability of the library and meet the user's demand for querying Chinese technology literature in natural language. This article proposes a two-stage method to implement the question answering system for Chinese technology literature. In the first stage, the Chinese question classification system based on sentence pattern is designed, and the stacking framework of ensemble learning algorithm is used to classify Chinese question. In the second stage, the pipeline is employed to parse the natural language question sentences and transfer them into Cypher statement. The field of "competitive intelligence" is selected for experiment. The experimental results show that the proposed stacking classification model improves the metric F1 by 10.81% compared with the single model average. Overall, the accuracy of translating Chinese questions into Cypher statements reached 83.96%. The proposed method can effectively convert Chinese questions into Cypher statements and directly return the answer to users. It provides a reference scheme for the application of the question answering based on knowledge map, which can improve the knowledge service ability of the library.
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Index Terms
- Research on Construction of Chinese Technology Literature Question Answering System Based on Knowledge Graph
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October 2023
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Published: 21 December 2023
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CSAE 2023
CSAE 2023: The 7th International Conference on Computer Science and Application Engineering
October 17 - 19, 2023
Virtual Event, China
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Overall Acceptance Rate 368 of 770 submissions, 48%
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