The Feasibility of Applying Prompt Engineering Based on Large Language Models in the Public Domain

With the rapid development of Large Language Models (LLMs), they have demonstrated powerful capabilities in fields such as natural language processing (NLP) and data mining. Currently, we are in an era of data explosion, with various types of data emerging in vast quantities. Data processing methods need to be constantly updated to adapt to the development of the times. This article aims to explore and focus on the existing LLMs, continuously attempting to change the prompt words from different angles, such as tone and providing context information, etc., to achieve different output effects.

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Published
2025-04-12
DOI
https://doi.org/10.1109/isssr65654.2025.00068
Primary Topic
Semantic Web and Ontologies
Type
article
Field-Weighted Citation Impact
0.00
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article

The Feasibility of Applying Prompt Engineering Based on Large Language Models in the Public Domain

Yuxiang Shen, Rongshang Chen, Lei Xiao, Yu Gao
Semantic Web and Ontologies
article

The Feasibility of Applying Prompt Engineering Based on Large Language Models in the Public Domain

Yuxiang Shen, Rongshang Chen, Lei Xiao, Yu Gao
article en

Abstract

With the rapid development of Large Language Models (LLMs), they have demonstrated powerful capabilities in fields such as natural language processing (NLP) and data mining. Currently, we are in an era of data explosion, with various types of data emerging in vast quantities. Data processing methods need to be constantly updated to adapt to the development of the times. This article aims to explore and focus on the existing LLMs, continuously attempting to change the prompt words from different angles, such as tone and providing context information, etc., to achieve different output effects.

Xiamen University of Technology (CN)
Openalex Percentile: Top 94%
Semantic Web and Ontologies
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