一、中文
劉冠妤(2018),基於聊天機器人之運動智能助理研究與開發,實踐大學資訊科技與管理學系碩士班。二、英文
Aust, H., Oerder, M., Seide, F., & Steinbiss, V. (1995). The Philips automatic train timetable information system. Speech Communication, 17(3-4), 249-262.
Bellegarda, J. R. (2013). Large-scale personal assistant technology deployment: the siri experience. In INTERSPEECH (pp. 2029-2033).
N. Bush, “The predictive value of transitional probability for word-boundary palatalization in English,” Unpublished M.S .thesis, Univ. New Mexico, Albuquerque, NM, 1999.
A. Berger, V. D. Pietra, and S. D. Pietra, “A maximum entropy approach to natural language processing,” Comput. Linguistics, vol. 22, no. 1, pp. 39–71, 1996.
Cahn, J. (2017). CHATBOT: Architecture, design, and development. University of Pennsylvania School of Engineering and Applied Science Department of Computer and Information Science.
Cho, K., Van Merriënboer, B., Gulcehre, C., Bahdanau, D., Bougares, F., Schwenk, H., & Bengio, Y. (2014). Learning phrase representations using RNN encoder-decoder for statistical machine translation. arXiv preprint arXiv:1406.1078.
Chouard, T. (2016). The Go Files: AI computer wraps up 4-1 victory against human champion. Nature News.
Chung, J., Gulcehre, C., Cho, K., & Bengio, Y. (2014). Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv preprint arXiv:1412.3555.
Colby, K. M., Weber, S., & Hilf, F. D. (1971). Artificial paranoia. Artificial Intelligence, 2(1), 1-25.
M. Dyer, “Connectionist natural language processing: A status report,” in Computational Architectures Integrating Neural and Symbolic Processes, R. Sun and L. Bookman, Eds. Dordrecht, The Netherlands: Kluwer Academic, 1995, vol. 292, pp. 389–429
Ginzburg, J., & Fernández, R. (2010). Computational models of dialogue. Handbook of Computational Linguistics and Natural Language, Oxford. Blackwell, 429-481.
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., ... & Bengio, Y. (2014). Generative adversarial nets. In Advances in neural information processing systems (pp. 2672-2680).
Goodfellow, I., Bengio, Y., Courville, A., & Bengio, Y. (2016). Deep learning (Vol. 1). Cambridge: MIT press.
Hochreiter, S., & Schmidhuber, J. (1997). Long short-term memory. Neural computation, 9(8), 1735-1780.
Jurafsky, D., & Martin, J. H. (2014). Speech and language processing (Vol. 3). London:: Pearson.
T. Joachims, Learning To Classify Text Using Support Vector Machines: Methods, Theory and Algorithms. Norwell, MA: Kluwer Academic, 2002.
LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. nature, 521(7553), 436-444.
LeCun, Y., Bottou, L., Bengio, Y., & Haffner, P. (1998). Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86(11), 2278-2324.
J. Lafferty, A. McCallum, and F. Pereira, “Conditional random fields: Probabilistic models for segmenting and labeling sequence data,” in Proc. 18th Int. Conf. Machine Learning, 2001, pp. 282–289.
Manning, C. D. & Schutze, H. (1999) Foundations of Statistical Natural Language Processing (MIT Press, Cambridge, MA).
McTear, M. F. (2002). Spoken dialogue technology: enabling the conversational user interface. ACM Computing Surveys (CSUR), 34(1), 90-169.
Michalski, R. S., Carbonell, J. G., & Mitchell, T. M. (Eds.). (2013). Machine learning: An artificial intelligence approach. Springer Science & Business Media.
Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013). Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781.
K. Nigam, A. McCallum, S. Thrun, and T. Mitchell, “Text classification from labeled and unlabeled documents using EM,” Machine Learn., vol. 39, nos. 2–3, pp. 103–134, 2000.
Papineni, K., Roukos, S., Ward, T., & Zhu, W. J. (2002). BLEU: a method for automatic evaluation of machine translation. In Proceedings of the 40th annual meeting on association for computational linguistics (pp. 311-318). Association for Computational Linguistics.
Pascanu, R., Mikolov, T., & Bengio, Y. (2012). Understanding the exploding gradient problem. CoRR, abs/1211.5063.
Reiter, E., & Dale, R. (2000). Building natural language generation systems. Cambridge university press.
Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986). Learning representations by back-propagating errors. nature, 323(6088), 533.
Schalkoff, R. J. (1997). Artificial neural networks (Vol. 1). New York: McGraw-Hill.
Serban, I. V., Sordoni, A., Bengio, Y., Courville, A. C., & Pineau, J. (2016). Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models. In AAAI (Vol. 16, pp. 3776-3784).
Seymore, K., McCallum, A., & Rosenfeld, R. (1999). Learning hidden Markov model structure for information extraction. In AAAI-99 workshop on machine learning for information extraction (pp. 37-42).
Shawar, B. A., & Atwell, E. (2007). Chatbots: are they really useful?. In Ldv forum (Vol. 22, No. 1, pp. 29-49).
Sutskever, I., Vinyals, O., & Le, Q. V. (2014). Sequence to sequence learning with neural networks. In Advances in neural information processing systems (pp. 3104-3112).
Turing, A. M. (1950). Computing Machinery And Intelligence. Mind, LIX(236), 433–460.
Wallace, R. S. (2009). The anatomy of ALICE. In Parsing the Turing Test (pp. 181-210). Springer, Dordrecht.
Weizenbaum, J. (1966). ELIZA—a computer program for the study of natural language communication between man and machine. Communications of the ACM, 9(1), 36-45.
Williams, R. J., & Zipser, D. (1989). A learning algorithm for continually running fully recurrent neural networks. Neural computation, 1(2), 270-280.
Young, S. J. (2000). Probabilistic methods in spoken–dialogue systems. Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 358(1769), 1389-1402.
三、網路
吳惠麟(2016),網管系統結合 LINE BOT 實現即時告警互動通知,取自於2017年8月14日,於http://www.netadmin.com.tw/article_content.aspx?sn=1610040003&jump=2。
唐子晴(2018),LINE台灣月活躍用戶破2,100萬,特愛三大功能、使用率名列全球第一,取自於2018年12月28日,於https://www.bnext.com.tw/article/51783/line-linetoday-linestore-sticker
民法,取自於2019年7月22日,https://zh.wikipedia.org/wiki/%E6%B0%91%E6%B3%95
Andrej Karpathy. (2015). The Unreasonable Effectiveness of Recurrent Neural Networks. Retrieved May 6, 2018, from http://karpathy.github.io/2015/05/21/rnn-effectiveness/
Carpenter, R. (2017). Cleverbot. Retrieved May 11, 2018 , from http://www.cleverbot.com/
Christopher Olah. (2015). Understanding LSTM Networks. Retrieved May 27, 2018, from
http://colah.github.io/posts/2015-08-Understanding-LSTMs/
Diditho. (2014). Technology Stack (Server) ‘Kompas TTS’. Retrieved October 5, 2017, from http://diditho.com/2014/12/10/technology-stack-aplikasi-kompas
Hugo Férée. (2011). Turing Test Version 3.svg. Retrieved May 20, 2018, from https://en.wikipedia.org/wiki/Computing_Machinery_and_Intelligence
LINE Corporation. (2017). LINE Developers. Retrieved May 16, 2017, from https://developers.Line.me/bot-api/overview
Microsoft. (2018). Xiaoice. Retrieved May 12, 2018, from https://poem.msxiaobing.com/
Radim Řehůřek. (2017). Gensim. Retrieved March 11, 2018, from https://radimrehurek.com/gensim/models/word2vec.html
Richard Wallace. (2011). AIML, Retrieved October 30, 2011, from https://en.wikipedia.org/wiki/AIML?fbclid=IwAR1e7lfs4B1Q6aRwnTOLOeWwTq34biSECnjNkaGNvJiRYKVdjLL55tIzAVc
Sun Junyi. (2017). Jieba. Retrieved May 20, 2017, from https://github.com/fxsjy/jieba
Thang Luong, Eugene Brevdo, Rui Zhao. (2018). Tensorflow.
Retrieved March 11, 2018, from https://www.tensorflow.org/tutorials/seq2seq