연구실의 새로운 연구가 preprint로 공개되었습니다. - Text Classiﬁcation using Capsules - 본 연구는 Capsule Network의 개념을 text classification에 적용한 초기 연구입니다. - 저자: Jaeyoung Kim, Sion Jang, Sungchul Choi(이상 TEAMLAB), Eunjeong Park(NAVER) - see: [researchgate](https://www.researchgate.net/publication/326985699_Text_Classification_using_Capsules), [arXiv](https://arxiv.org/abs/1808.03976) This paper presents an empirical exploration of the use of capsule networks for text classification. While it has been shown that capsule networks are effective for image classification, their validity in the domain of text has not been explored. In this paper, we show that capsule networks indeed have the potential for text classification and that they have several advantages over convolutional neural networks. We further suggest a simple routing method that effectively reduces the computational complexity of dynamic routing. We utilized seven benchmark datasets to demonstrate that capsule networks, along with the proposed routing method provide comparable results.