@inproceedings{c9d69c2973e14b1c8e3b73ead2b40f1b,
title = "A CONCEPT UTILITY FRAMEWORK FOR INCREMENTAL ONTOLOGY EXPANSION",
abstract = "A good medical ontology is expected to cover its domain completely and correctly. On the other hand, large ontologies are hard to build, hard to understand, and hard to maintain. Thus, adding new concepts (often multi-word concepts) to an existing ontology must be done judiciously. In this research, we propose a two-stage framework for evaluating candidate concepts for ontology expansion. The framework first employs a utility function that evaluates each candidate concept based on Semantic Relevance and Redundancy Avoidance. For candidates that meet a minimum utility threshold, a secondary Goodness Function is applied to evaluate an additional qualitative aspect, namely contextual fit. This framework of combining a utility metric with a goodness metric will be helpful for expert staff working on maintaining and extending ontologies. This systematic approach will enable the incremental expansion of ontologies while maintaining both depth and contextual relevance by integrating only concepts with high {"}utility{"}.",
keywords = "Concept Goodness, Concept Utility, Medical Ontology, Ontology Expansion, Ontology Metrics",
author = "Naren Khatwani and Lijing Wang and James Geller",
note = "Publisher Copyright: {\textcopyright} 2025 IADIS Press All rights reserved.; 10th International Conferences on Big Data Analytics, Data Mining and Computational Intelligence, BigDaCI 2025; 11th International Conference on Connected Smart Cities, CSC 2025 and 17th International Conference on e-Health, EH 2025 - part of the 19th Multi Conference on Computer Science and Information Systems 2025 ; Conference date: 23-07-2025 Through 25-07-2025",
year = "2025",
language = "English (US)",
series = "Proceedings of the International Conferences on Big Data Analytics, Data Mining and Computational Intelligence 2025, BigDaCI 2025; Connected Smart Cities 2025 and e-Health 2025, EH 2025 - part of the Multi Conference on Computer Science and Information Systems 2025",
publisher = "IADIS",
pages = "237--241",
editor = "Ajith Abraham and Peng, \{Guo Chao\} and Pedro Isaias and Luis Rodrigues",
booktitle = "Proceedings of the International Conferences on Big Data Analytics, Data Mining and Computational Intelligence 2025, BigDaCI 2025; Connected Smart Cities 2025 and e-Health 2025, EH 2025 - part of the Multi Conference on Computer Science and Information Systems 2025",
}