Research on knowledge full-text retrieval engine technology based on Elasticsearch

Ying Liu; Qi Chen; Xiaolu Zhou; Danping Li

doi:10.1117/12.3038173

7 August 2024 Research on knowledge full-text retrieval engine technology based on Elasticsearch

Ying Liu, Qi Chen, Xiaolu Zhou, Danping Li

Proceedings Volume 13229, Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024); 1322918 (2024) https://doi.org/10.1117/12.3038173
Event: Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024), 2024, Nanchang, China

Abstract

After years of accumulation, our department has accumulated a large amount of knowledge, which is stored in Oracle and MongoDB database and uniformly displayed in the knowledge management app of the IT Service Management (ITSM) System. In order to quickly and efficiently search for knowledge, this project is based on Elasticsearch (ES) and implements a knowledge full-text retrieval system. Compared to traditional SQL based retrieval methods, the retrieval platform built in this project is capable of retrieving knowledge attachment content and sorting it by relevance. The implementation effect after deployment shows that it can effectively improve the efficiency of knowledge retrieval and effectively display the hit content in attachments.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ying Liu, Qi Chen, Xiaolu Zhou, and Danping Li "Research on knowledge full-text retrieval engine technology based on Elasticsearch", Proc. SPIE 13229, Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024), 1322918 (7 August 2024); https://doi.org/10.1117/12.3038173

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