Effect of text color on word embeddings

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

抄録

In natural scenes and documents, we can find a correlation between text and its color. For instance, the word, “hot,” is often printed in red, while “cold” is often in blue. This correlation can be thought of as a feature that represents the semantic difference between the words. Based on this observation, we propose the idea of using text color for word embeddings. While text-only word embeddings (e.g. word2vec) have been extremely successful, they often represent antonyms as similar since they are often interchangeable in sentences. In this paper, we try two tasks to verify the usefulness of text color in understanding the meanings of words, especially in identifying synonyms and antonyms. First, we quantify the color distribution of words from the book cover images and analyze the correlation between the color and meaning of the word. Second, we try to retrain word embeddings with the color distribution of words as a constraint. By observing the changes in the word embeddings of synonyms and antonyms before and after re-training, we aim to understand the kind of words that have positive or negative effects in their word embeddings when incorporating text color information.

本文言語英語
ホスト出版物のタイトルDocument Analysis Systems - 14th IAPR International Workshop, DAS 2020, Proceedings
編集者Xiang Bai, Dimosthenis Karatzas, Daniel Lopresti
出版社Springer
ページ341-355
ページ数15
ISBN(印刷版)9783030570576
DOI
出版ステータス出版済み - 2020
イベント14th IAPR International Workshop on Document Analysis Systems, DAS 2020 - Wuhan, 中国
継続期間: 7 26 20207 29 2020

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
12116 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

会議

会議14th IAPR International Workshop on Document Analysis Systems, DAS 2020
国/地域中国
CityWuhan
Period7/26/207/29/20

All Science Journal Classification (ASJC) codes

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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