Earticle

초록

영어

In Business Intelligence (BI) environments, organizations increasingly face challenges in integrating data distributed across multiple heterogeneous domains. Traditional systems mainly address structural or schemalevel differences. However, they often overlook inconsistencies in the meanings of domain-specific terms. These limitations can lead to misinterpretation and reduce the effectiveness of data analysis. To address these issues, we designed and propose a meaning-based inter-domain mapping system. This system enables semantic integration across multiple domains. First, it collects distributed domain information from various sources. Then, it measures semantic similarity between fields using text embeddings and cosine similarity, and clusters related fields into groups. Representative meaning units are selected for each cluster and stored in a central domain repository, which supports consistent interpretation and semantic queries. By focusing on meaning rather than solely on structure, the system ensures more accurate and efficient data utilization. It also reduces redundancy and semantic ambiguity, supporting better decision-making in BI analyses. Experimental evaluation shows that the system effectively consolidates semantically similar domains and enhances analytical reliability.

목차

Abstract
1. Introduction
2. Related Work
3. Proposed System
3.1 System Overview
3.2 Sequence Diagram
4. Performance Analysis
5. Discussions
6. Conclusion
Acknowledgement
References

키워드

저자

• Sa-rang Lee [ The Master’s course, Graduate School of Smart Convergence, Kwangwoon University, Seoul, Korea ]
• Seok-Jae Moon [ Professor, Graduate School of Smart Convergence, Kwangwoon University, Seoul, Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Internet, Broadcasting and Communication

• 간기

  계간

• pISSN

  2288-4920

• eISSN

  2288-4939

• 수록기간

  2009~2025

• 십진분류

  KDC 326 DDC 380