EREO: An Effective Rule Evaluation Framework for Discovering Interesting Patterns in US Birth Data and Beyond

Abhilash C. B., Kavi Mahesh

2023

Abstract

Birth data holds immense importance in healthcare for several reasons. It offers a comprehensive and representative sample of the population, enabling the identification of patterns and trends that can significantly impact public health policies and interventions. However, extracting interesting patterns from the vast birth data attributes poses a domain-specific and challenging problem. We can derive intriguing patterns by utilizing rare rules for identifying interesting associations. The level of interestingness depends on various factors, including the user, data, and domain. To address this, we propose the Effective Rule Evaluation using Ontology (EREO) framework, which incorporates two modes of rule evaluation. Firstly, the Integrated Rule Information Content (IRIC) measure is employed to quantify the level of interestingness. Secondly, the interesting rules are assessed by domain experts. The combined approach of these two modes of evaluation confirms the level of interestingness of the derived rules.The study demonstrates a significant relationship between these two modes of assessment, providing evidence of the convergence between expert evaluations and the ontology-based association rule measurements. This connection adds further value to the field by contributing to the understanding and measurement of interestingness within the context of ontology-based association rules

Paper Citation

in Harvard Style

C. B. A. and Mahesh K. (2023). EREO: An Effective Rule Evaluation Framework for Discovering Interesting Patterns in US Birth Data and Beyond. In Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA; ISBN 978-989-758-664-4, SciTePress, pages 568-575. DOI: 10.5220/0012137400003541

in Bibtex Style

@conference{data23,
author={Abhilash C. B. and Kavi Mahesh},
title={EREO: An Effective Rule Evaluation Framework for Discovering Interesting Patterns in US Birth Data and Beyond},
booktitle={Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA},
year={2023},
pages={568-575},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012137400003541},
isbn={978-989-758-664-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA
TI - EREO: An Effective Rule Evaluation Framework for Discovering Interesting Patterns in US Birth Data and Beyond
SN - 978-989-758-664-4
AU - C. B. A.
AU - Mahesh K.
PY - 2023
SP - 568
EP - 575
DO - 10.5220/0012137400003541
PB - SciTePress