Document Type
Article
Date
2024
Keywords
Gene Ontology, knowledgebases, machine learning, dataset design and creation
Language
English
Disciplines
Health Sciences and Medical Librarianship | Library and Information Science
Description/Abstract
This demo proposal presents a case study that uses Gene Ontology (GO) and ML/AI algorithms to design and create KO-derived datasets for ML/AI applications. We discuss the characteristics and requirements of KO practices and products in implementing ML algorithms. The focus of this demo is on how knowledge organization systems can be utilized to derive datasets that can deliver quality and trustworthiness for achieving the precision, computing of semantic similarity, and interoperability in these algorithms.
Recommended Citation
Liu, Qiaoyi and Qin, Jian, "Using Gene Ontology and ML Algorithms for Dataset Design and Creation for ML/AI Modeling" (2024). School of Information Studies - Post-doc and Student Scholarship. 21.
https://surface.syr.edu/ischoolstudents/21
Source
submission
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
