@inproceedings{e36e311688344585927ed718ba39487d,
title = "Transient Detection Modeling as Imbalance Data Classification",
abstract = "Acquisition of large astronomical data prompted astronomers to join the global trend of big data science and artificial intelligence. The Gravitational-wave Optical Transient Observers is a visual counterpart in capturing transient events provides millions of observed sources which are then systematically process and analyze in reference to simulated data in order to identify real sources. Basically, this study focuses in utilizing conventional data mining applications.",
keywords = "classification, imbalance class, sky survey, transient detection",
author = "Tabacolde, {Aireen B.} and Tossapon Boongoen and Natthakan Iam-On and James Mullaney and Utane Sawangwit and Krzysztof Ulaczyk",
note = "Funding Information: This work is funded by ST/P005594/1 - Newton STFC-NARIT: Using astronomy surveys to train Thai researchers in Big Data analysis; and partly funded by Mae Fah Luang University. Publisher Copyright: {\textcopyright} 2018 IEEE.; 1st IEEE International Conference on Knowledge Innovation and Invention, ICKII 2018 ; Conference date: 23-07-2018 Through 27-07-2018",
year = "2018",
month = dec,
day = "7",
doi = "10.1109/ICKII.2018.8569123",
language = "English",
series = "1st IEEE International Conference on Knowledge Innovation and Invention, ICKII 2018",
publisher = "IEEE Press",
pages = "180--183",
editor = "Teen-Hang Meen",
booktitle = "1st IEEE International Conference on Knowledge Innovation and Invention, ICKII 2018",
address = "United States of America",
}