A Multi Class Classification to Detect Original Form of Kaomoji using Neural Network

Noriyuki Okumura, Rei Okumura

2019

Abstract

In this paper, we propose a multi-class classification method for Kaomoji using feed forward neural network. Neural network has some units in each layer, but the suitable number of units is not clear. This research investigated the relation between the number of units and the accuracy of multi-class classification method.

Paper Citation

in Harvard Style

Okumura N. and Okumura R. (2019). A Multi Class Classification to Detect Original Form of Kaomoji using Neural Network. In Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 3: KMIS; ISBN 978-989-758-382-7, SciTePress, pages 377-382. DOI: 10.5220/0008366203770382

in Bibtex Style

@conference{kmis19,
author={Noriyuki Okumura and Rei Okumura},
title={A Multi Class Classification to Detect Original Form of Kaomoji using Neural Network},
booktitle={Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 3: KMIS},
year={2019},
pages={377-382},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008366203770382},
isbn={978-989-758-382-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 3: KMIS
TI - A Multi Class Classification to Detect Original Form of Kaomoji using Neural Network
SN - 978-989-758-382-7
AU - Okumura N.
AU - Okumura R.
PY - 2019
SP - 377
EP - 382
DO - 10.5220/0008366203770382
PB - SciTePress