Abstract
With the growing importance of dialog system and personal assistance systems (e.g. Google Now or Amazon Alexa) chatbots arrive more and more in the focus of interest. Current chatbots are typically tailored for specific scenarios and rather simple questions and commands. These systems cannot readily handle application domains characterized by a large number of relevant facts and complex services (e.g., offered by the public administration).
In this work, we present a chatbot framework tailored specifically to the needs of public administrations able to provide answers for all types of questions related to offered services and offices. The challenges in this scenario are the large number of relevant services, the complexity of administrative services, the context-dependent relevance of user questions, the differences in expert-language and user-language as well as the necessity of providing highly reliable answers for all questions.
We present the developed framework and discuss our experiences obtained while running the chatbot publicly with real users. The results show that our system efficiently provides relevant answers to the user questions. We explain how our system extends existing approaches and discuss the experiences with the live system.
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References
Abdul-Kader, S.A., Woods, D.J.: Survey on chatbot design techniques in speech conversation systems. Int. J. Adv. Comput. Sci. Appl. 6(7), 72–80 (2015). https://doi.org/10.14569/IJACSA.2015.060712
Allam, A.M.N., Haggag, M.H.: The question answering systems: a survey. Int. J. Res. Rev. Inf. Sci. 2(3), 211–221 (2012)
Bi, Y., Deng, K., Cheng, J.: A keyword-based method for measuring sentence similarity. In: Proceedings of the 2017 ACM on Web Science Conference, WebSci 2017, pp. 379–380. ACM, New York (2017)
Chia, A.: 5 reasons to use the gov.sg bot, March 2017. Blog of Singapore Government. https://www.gov.sg/news/content/5-reasons-to-use-the-gov-sg-bot
Cui, L., Huang, S., Wei, F., Tan, C., Duan, C., Zhou, M.: Superagent: a customer service chatbot for e-commerce websites. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017, Vancouver, Canada, 30 July–4 August, System Demonstrations, pp. 97–102 (2017)
Deutscher Bundestag. Gesetz zur Förderung der elektronischen Verwaltung sowie zur Änderung weiterer Vorschriften. Bundesgesetzblatt (German Federal Law Gazette), Section 1, 25 July 2013
Kaid, L.L., Holtz-Bacha, C. (eds.): Encyclopedia of Political Communication, Part I, chapter E-Government, pp. 200–204. SAGE (2008). ISBN 978-1412917995
Magistrat der Stadt Wien. WienBot - Der Chatbot der Stadt, June 2017. https://www.wien.gv.at/bot/
Mishra, A., Jain, S.K.: A survey on question answering systems with classification. J. King Saud Univ. Comput. Inf. Sci. 28(3), 345–361 (2016)
Qiu, M., Li, F.-L., Wang, S., Gao, X., Chen, Y., Zhao, W., Chen, H., Huang, J., Chu, W.: AliMe chat: a sequence to sequence and rerank based chatbot engine. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, pp. 498–503. Association for Computational Linguistics (2017)
Zhai, C., Massung, S.: Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining. Association for Computing Machinery and Morgan, Claypool, New York, NY, USA (2016)
Acknowledgment
We thank the ITDZ Berlin for supporting the development and the optimization of the chatbot framework.
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Lommatzsch, A. (2018). A Next Generation Chatbot-Framework for the Public Administration. In: Hodoň, M., Eichler, G., Erfurth, C., Fahrnberger, G. (eds) Innovations for Community Services. I4CS 2018. Communications in Computer and Information Science, vol 863. Springer, Cham. https://doi.org/10.1007/978-3-319-93408-2_10
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DOI: https://doi.org/10.1007/978-3-319-93408-2_10
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