A Flexible Weighting Framework For Converting Relational Database To Hypergraphs

We propose a framework for converting relational databases (RDB) into hypergraphs to adjust and output various PageRank (PR) correlations by weighting hyperedges and nodes. While analyzing PR of converted graphs can reveal multifaceted information about relationships in the data, conventional methods struggled to balance the correlations between node PR and degree (NPR correlation) and edge PR and shared field records (EPR correlation). Our approach introduces two exponential weighting parameters: α for edge size, influencing EPR correlation, and β for node degree, influencing NPR correlation. By adjusting these parameters, various PR correlations can be obtained. Evaluation using real-world data demonstrate that our model can convert RDBs into hypergraphs with flexibility.

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Publication Details

Published
2025-01-15
DOI
https://doi.org/10.1109/icoin63865.2025.10993172
Citations
2
Primary Topic
Data Mining Algorithms and Applications
Type
article
Field-Weighted Citation Impact
6.49
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article

A Flexible Weighting Framework For Converting Relational Database To Hypergraphs

Kotaro Fujii, Tsuyoshi Yamashita, Andrew Shin, Kunitake Kaneko
2 citations
Data Mining Algorithms and Applications
6.49
article

A Flexible Weighting Framework For Converting Relational Database To Hypergraphs

Kotaro Fujii, Tsuyoshi Yamashita, Andrew Shin, Kunitake Kaneko
article en
2 citations

Abstract

We propose a framework for converting relational databases (RDB) into hypergraphs to adjust and output various PageRank (PR) correlations by weighting hyperedges and nodes. While analyzing PR of converted graphs can reveal multifaceted information about relationships in the data, conventional methods struggled to balance the correlations between node PR and degree (NPR correlation) and edge PR and shared field records (EPR correlation). Our approach introduces two exponential weighting parameters: α for edge size, influencing EPR correlation, and β for node degree, influencing NPR correlation. By adjusting these parameters, various PR correlations can be obtained. Evaluation using real-world data demonstrate that our model can convert RDBs into hypergraphs with flexibility.

Keio University (JP)
Openalex Percentile: Top 4%
Data Mining Algorithms and Applications
6.49
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