Abstract
As the information in the internet proliferates, the methods for effectively providing the information have been exploited, especially in conversational agents. Bayesian network is applied to infer the intention of user’s query. Since the construction of Bayesian network requires large efforts and much time, an automatic method for it might be useful for applying conversational agents to several applications. In order to improve the scalability of the agent, in this paper, we propose a method of automatically generating Bayesian networks from scripts composing knowledge base of the conversational agent. It constructs the structure of hierarchically composing nodes and learns the conditional probability distribution table using Noisy-OR gate. The experimental results with subjects confirm the usefulness of the proposed method.
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Lee, S.-I., Sung, C., Cho, S.-B.: An effective conversational agent with usermodeling based on Bayesian network. In: Zhong, N., Yao, Y., Ohsuga, S., Liu, J. (eds.) WI 2001. LNCS (LNAI), vol. 2198, pp. 428–432. Springer, Heidelberg (2001)
Macskassy, S., Stevenson, S.: A conversational agent. Master Essay. Rutgers University (1996)
Heckerman, D.: A tutorial on learning Bayesian networks. Tech. rep., Microsoft Research, Advanced Technology Division (1995)
Cooper, G.F.: A simple constraint-based algorithm for efficiently mining observational databases for causal relationships. Data Mining and Knowledge Discovery 1, 203–224 (1997)
Xiang, Y., Chu, T.: Parallel learning of belief networks in large and difficult domains. Data Mining and Knowledge Discovery 3, 315–339 (1999)
Silverstein, C., Brin, S., Motwani, R., Ullman, J.: Scalable techniques for mining causal structures. Data Mining and Knowledge Discovery 4, 163–192 (2000)
Allen, J., Byron, D., Dzikovska, M., Ferguson, G., Galescu, L., Stent, A.: Towards conversational human-computer interaction. AI Magazine 22(4), 27–38 (2001)
Weizenbaun, J.: ELIZA - A computer program for the study of natural language communication between man and machine. Communications of the ACM 9(1), 36–45 (1965)
Horvitz, E., Breese, J., Heckerman, D., Hovel, D., Rommelse, K.: The lumiere project: Bayesian user modeling for inferring the goals and needs of software users. In: Proc. of the 14th Conf. Uncertainty in Artificial Intelligence, pp. 256–265 (1998)
Hong, J.-H., Cho, S.-B.: A two-stage Bayesian network for effective development of conversational agent. Lecture Note in Computer Science, vol. 2690, pp. 1–8. Springer, Heidelberg (2003)
Chai, J., Horvath, V., Nicolov, N., Budzikowska, M., Kambhatla, N., Zadrozny, W.: Natural language sales assistant: A web-based dialog system for online sales. In: Proc. of the 13th Annual Conf. on Innovative Applications of Artificial Intelligence, pp. 19–26 (2001)
Paek, T., Horvitz, E.: Conversation as action under uncertainty. In: Proc. of the 16th Conf. on Uncertainty in Artificial Intelligence, pp. 455–464 (2000)
Heckerman, D.: A tutorial on learning with Bayesian networks. Microsoft Research, Technical Report MSR-TR-95-06 (1995)
Horvitz, E., Paek, T.: A computational architecture for conversation. In: Proc. of the 7th Int. Conf. on User Modeling, pp. 201–210 (1999)
Allen, J.: Mixed initiative interaction. IEEE Intelligent Systems 14(6), 14–23 (1999)
Wu, X., Zheng, F., Xu, M.: TOPIC Forest: A plan-based dialog management structure. In: Int. Conf. on Acoustics, Speech and Signal Processing, pp. 617–620 (2001)
Onisko, A., Druzdzel, M.J., Wasyluk, H.: Learning Bayesian network parameters from small data sets: Application of noisy-OR gates. Int. Journal of Approximate Reasoning 27(2), 165–182 (2001)
Genie2 & Smile, http://www.sis.pitt.edu/~genie/
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Lim, S., Cho, SB. (2005). Automatic Construction of Bayesian Networks for Conversational Agent. In: Huang, DS., Zhang, XP., Huang, GB. (eds) Advances in Intelligent Computing. ICIC 2005. Lecture Notes in Computer Science, vol 3645. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11538356_24
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DOI: https://doi.org/10.1007/11538356_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28227-3
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