지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- Korean Institute of Information Scientists and Engineers Journal of Computing Science and Engineering Journal of Computing Science and Engineering Vol.16 No.3
- 발행연도
- 2022.9
- 수록면
- 165 - 177 (13page)
- DOI
- 10.5626/JCSE.2022.16.3.165
이용수
초록· 키워드
오류제보하기
Text visualization is a complex technique that helps in data understanding and insight, and may lead to loss of information. Through the proposed low-dimensional vector representation learning method, deep learning and visualization through low-dimensional vector space construction were simultaneously performed. This method can transform a task-oriented dialogue dataset into low-dimensional coordinates, and based on this, a deep learning vector space can be constructed. The low-dimensional vector representation deep learning model found the intent of a sentence within a dataset and predicted the sentence components well in 3 out of 5 datasets. In addition, by checking the prediction results in the low-dimensional vector space, it was possible to improve the understanding of the data, such as identifying the structure or errors in the data.
목차
Abstract
I. INTRODUCTION
II. RELATED WORK
III. DATA ANALYSIS
IV. COORDINATE TRANSFORMATION ALGORITHMS FOR VISUALIZATION
V. EXPERIMENT
VI. DISCUSSION
VII. CONCLUSION
REFERENCES
참고문헌 (16)
참고문헌 신청
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F. Brad, R. Iacob, I. Hosu, and T. Rebedea, “Dataset for a neural natural language interface for databases (NNLIDB),” 2017 [Online]. Available: https://arxiv.org/abs/1707.03172.
J. J. Van Wijk, “The value of visualization,” in Proceedings of IEEE Visualization, Minneapolis, MN, 2005, pp. 79-86.
L. McInnes, J. Healy, and J. Melville, “UMAP: uniform manifold approximation and projection for dimension reduction,” 2018 [Online]. Available: https://arxiv.org/abs/1802.03426.
L. Van der Maaten and G. Hinton, “Visualizing data using t-SNE,” Journal of Machine Learning Research, vol. 9, pp. 2579-2605, 2008.
F. Brad, R. Iacob, I. Hosu, and T. Rebedea, “Dataset for a neural natural language interface for databases (NNLIDB),” 2017 [Online]. Available: https://arxiv.org/abs/1707.03172.
J. J. Van Wijk, “The value of visualization,” in Proceedings of IEEE Visualization, Minneapolis, MN, 2005, pp. 79-86.
L. McInnes, J. Healy, and J. Melville, “UMAP: uniform manifold approximation and projection for dimension reduction,” 2018 [Online]. Available: https://arxiv.org/abs/1802.03426.
L. Van der Maaten and G. Hinton, “Visualizing data using t-SNE,” Journal of Machine Learning Research, vol. 9, pp. 2579-2605, 2008.
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