Sentence Recommendation Using Beam Search in a Military Intelligent Image Analysis System |
Na, Hyung-Sun
(광운대학교 인공지능융합학과)
Jeon, Tae-Hyeon (호서대학교 컴퓨터공학과) Kang, Hyung-Seok (국방과학연구소) Ahn, Jinhyun (제주대학교 경영정보학과) Im, Dong-Hyuk (광운대학교 정부융합학부) |
1 | S. Wiseman and A. M. Rush. "Sequence -to-sequence learning as beam-search optimization," Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016. |
2 | pyhwp Documentation 2013. [Internet], https://pythonhosted.org/pyhwp/ko/ (accessed August 2, 2021.) |
3 | P. Bojanowski, E. Grave, A. Joulin, and T. Mikolov, "Enriching word vectors with subword information," Transactions of the Association for Computational Linguistics, Vol.5, pp.135-146, 2017. DOI |
4 | E. J. Park and S. Z. Cho, "KoNLPy: Korean natural language processing in Python," Annual Conference on Human and Language Technology, pp.133-136, 2014. |
5 | I. Sutskever, O. Vinyals, and V. L. Quoc, "Sequence to sequence learning with neural networks," In: Advances in neural Information Processing Systems, pp.3104-3112, 2014. |
6 | K. Palasundram, N. M. Sharef, N. Nasharuddin, K. Kasmiran, and A. Azman "Sequence to sequence model performance for education chatbot," International Journal of Emerging Technologies in Learning (iJET), Vol.14, No.24, pp.56-68, 2019. |
7 | T. H. Jeon, H. S. Na, J. H. Ahn, and D. H. Im, "Pre-processing and implementation for intelligent imagery interpretation system," Proceedings of the Korea Information Processing Society Conference, Vol.28, pp.305-307, 2021. |
8 | M. Zhang, Z. Li, G. Fu, and M. Zhang, "Syntax-enhanced neural machine translation with syntax-aware word representations," Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Vol.1 (Long and Short Papers), 2019. |
9 | D. Bahdanau, C. Kyunghyun, and Y. Bengio, "Neural machine translation by jointly learning to align and translate," 3rd International Conference on Learning Representations, ICLR 2015. |
10 | Y. D. Kim and H. J. Gwon, "A study on defense command and control system AI application," Korea Information Processing Society Review, Vol.24, No.1, pp.13-18, 2017. |
11 | K. Qian and Z. Yu. "Domain adaptive dialog generation via meta learning," Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019. |
12 | Comparison of Korean stemming analyzer performance (2018). [Internet], https://iostream.tistory.com/144 (accessed August 2, 2021) |
13 | T. Mikolov, K. Chen, G Corrado, and J. Dean, "Efficient estimation of word representations in vector space," arXiv preprint arXiv:1301.3781, 2013. |
14 | Y. Bengio, R. Ducharme, P. Vincent, and C. Jauvin, "A neural probabilistic language model," Journal of Machine Learning Research, Vol.3, 1137-1155, 2003. |
15 | S. Hochreiter and J. Schmidhuber, "Long short-term memory," Neural Computation, Vol.9, No.8, pp.1735-1780, 1997. DOI |
16 | J. Chung, C. Gulcehre, K. Cho, and Y. Bengio, "Empirical evaluation of gated recurrent neural networks on sequence modeling." NIPS 2014 Workshop on Deep Learning, Dec. 2014. |
17 | K. Cho, "Noisy parallel approximate decoding for conditional recurrent language model," arXiv preprint arXiv:1605.03835, 2016. |
18 | J. Pennington, R. Socher, and C. D. Manning, "Glove: Global vectors for word representation," Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, pp.1532-1543, 2014. |
19 | Y. Bengio, P. Simard, and P. Frasconi, "Learning long-term dependencies with gradient descent is difficult." IEEE Transactions on Neural Networks, Vol.5, No.2, pp.157-166, 1994. DOI |
20 | S. Mangal, P. Joshi, and R. Modak, "Lstm vs. gru vs. bidirectional rnn for script generation," arXiv preprint arXiv: 1908.04332, 2019. |
21 | T. Mikolov, M. Karafiat, L. Burget, J. Cernocky, and S. Khudanpur, "Recurrent neural network based language model," In Eleventh Annual Conference of the International Speech Communication Association, Vol.9, pp.1045-1048, 2010. |