A Large Scale Knowledge Base Representing the Base Form of Kaomoji

Noriyuki Okumura

2017

Abstract

In this paper, we construct a large-scale knowledge base representing the base form of kaomoji (emoticon) and other elements of kaomoji: eye, nose, mouth, and so on, to analyze features of kaomoji in detail. Previous methods to analyze kaomoji mainly aim to extract kaomoji from sentences, paragraphs, or documents, or to classify kaomoji into some emotion classes based on the emotion that kaomoji shows or potentially includes. We define the base form of kaomoji for detailed kaomoji analytics. Application systems can estimate another feature of derivative kaomoji based on its base form and other elements for sentiment analytics, emotion extraction, or kaomoji classification. We annotated about 40,000 kinds of kaomoji for constructing a largescale knowledge base. The total number of extracted base forms is about 3,000. In experimental evaluations based on cosine similarity using N-gram based features and simple Skip-gram based features, we show that the model can estimate the base form of kaomoji with an accuracy of about 50%.

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Paper Citation


in Harvard Style

Okumura N. (2017). A Large Scale Knowledge Base Representing the Base Form of Kaomoji.In Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, ISBN 978-989-758-272-1, pages 246-252. DOI: 10.5220/0006517002460252


in Bibtex Style

@conference{keod17,
author={Noriyuki Okumura},
title={A Large Scale Knowledge Base Representing the Base Form of Kaomoji},
booktitle={Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD,},
year={2017},
pages={246-252},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006517002460252},
isbn={978-989-758-272-1},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD,
TI - A Large Scale Knowledge Base Representing the Base Form of Kaomoji
SN - 978-989-758-272-1
AU - Okumura N.
PY - 2017
SP - 246
EP - 252
DO - 10.5220/0006517002460252