Prototyping a Chatbot for Student Supervision in a Pre-Registration Process

Authors

  • Lucia Dwi Krisnawati IT Department, Duta Wacana Christian University Yogyakarta, Indonesia
  • Bill Edward Butar-Butar
  • Gloria Virginia It Department Duta Wacana Christian University Yogyakarta Indonesia

DOI:

https://doi.org/10.21512/commit.v12i2.4813

Keywords:

Chatbots, Dialogue System, Keyword- Spotting Technique, Transducer

Abstract

Developing a chatbot becomes a challenging task when it is built from scratch and independent of any Software as a Service (SaaS). Inspired by the idea of freeing lecturers from the burden of answering the same questions repetitively during the pre-registration process, this research has succeeded in building a textbased chatbot system. Further, this research has proved that the combination of keyword spotting technique for the Language Understanding component, Finite-State Transducer (FST) for the Dialogue Management, rulebased keyword matching for language generation, and the system-in-the-loop paradigm for system validation can produce an efficient chatbot. The chatbot efficiency is high enough as its score on Concept Efficiency (CE) reaches 0.946. It shows that users do not need to repeat their utterances several times to be understood. The chatbot performance on recognizing new concepts introduced by users is also more than satisfactory which is presented by its Query Density (QD) score of 0.80.

Dimensions

Plum Analytics

Author Biography

Lucia Dwi Krisnawati, IT Department, Duta Wacana Christian University Yogyakarta, Indonesia

An assistant professor (Lektor) in Natural Language Processing, Text forensics, Optical Charater Recognition, Machine Learning and Digital Humanities. She also is a past director of Dual Degree Program on Information Technology (IDDIT) Duta Wacana Christian University. She received her Doctoral degree on Natural Language Processing from Ludwig Maximilian University (LMU), Munich, Germany. She received her Magister and Vordiplome on the same field from LMU also. She has done her first undergraduate program (S1) in English Literature, Gadjah Mada University, Jogjakarta. She has received several scholarship for supporting her studies abroad such as DAAD, EED, OESW. All are German-based scholarship boards. 

References

D. Allison, “Chatbots in the library: Is it time?” Library Hi Tech, vol. 30, no. 1, pp. 95–107, 2012.

J. Cahn, “CHATBOT: Architecture, design, & development,” 2017, University of Pennsylvania.

J. Constine and S. Perez. (2016) Facebook Messenger now allows payments in its 30,000 chatbots. [Online]. Available: https://techcrunch. com/2016/09/12/messenger-bot-payments/

kata.ai. (2018) Studi kasus chatbot: Pelajari bagaimana chatbot membantu perusahaan mencapai tujuan bisnisnya. [Online]. Available: https://kata.ai/case-studies/

A. Bartl and G. Spanakis, “A retrieval-based dialogue system utilizing utterance and context embeddings,” in 16th IEEE International Conference on Machine Learning and Applications (ICMLA). IEEE, Dec.18–21, 2017, pp. 1120–1125.

N. M. Radziwill and M. C. Benton, “Evaluating quality of chatbots and intelligent conversational agents,” ArXiv Preprint ArXiv:1704.04579, 2017.

M. L. McNeal and D. Newyear, “Introducing chatbots in libraries,” Library Technology Reports, vol. 49, no. 8, pp. 5–10, 2013.

M. McTear, Z. Callejas, and D. Griol, The conversational interface: Talking to smart devices. Switzerland: Springer, 2016.

T. Kl¨uwer, “From chatbots to dialog systems,” in Conversational agents and natural language interaction: Techniques and effective practices. IGI Global, 2011, pp. 1–22.

S. A. Abdul-Kader and J. Woods, “Survey on chatbot design techniques in speech conversation systems,” International Journal of Advanced Computer Science and Applications, vol. 6, no. 7, pp. 72–80, 2015.

A. Niklasson, “Dialogue systems using webbased language tools,” Master’s thesis, Umea University, Sweden, 2017.

S. Ghose and J. J. Barua, “Toward the implementation of a topic specific dialogue based natural language chatbot as an undergraduate advisor,” in International Conference on Informatics, Electronics & Vision (ICIEV). Dhaka, Bangladesh: IEEE, May 17–18, 2013, pp. 1–5.

B. Setiaji and F. W. Wibowo, “Chatbot using a knowledge in database: Human-to-machine conversation modeling,” in 7th International Conference on Intelligent Systems, Modelling and Simulation, Bangkok, Thailand, March 16, 2016, pp. 72–77.

L. D. Krisnawati, “Implementing mixed initiative dialogue in voiceXML to process CIS queries,” in Seminar Nasional Sistem dan Informatika, Bali, Nov. 16, 2007, pp. 149–155.

M. Dahiya, “A tool of conversation: Chatbot,” International Journal of Computer Sciences and Engineering, vol. 5, no. 5, pp. 158–161, 2017.

F. Morbini, E. Forbell, D. DeVault, K. Sagae, D. R. Traum, and A. A. Rizzo, “A mixedinitiative conversational dialogue system for healthcare,” in Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue. Seoul, South Korea: Association for Computational Linguistics, July 5–6, 2012, pp. 137–139.

D. Griol and J. M. Molina, “A proposal to manage multi-task dialogs in conversational interfaces,” Advances in Distributed Computing and Artificial Intelligence Journal (ADCAIJ), vol. 5, no. 2, pp. 53–65, 2016.

M. Hirzel, L. Mandel, A. Shinnar, J. Simon, and M. Vaziri, “I can parse you: Grammars for dialogs,” in 2nd Summit on Advances in Programming Languages (SNAPL), Yorktown Heights, USA, May 9, 2017, pp. 6:1–6:15.

Z. Yan, N. Duan, P. Chen, M. Zhou, J. Zhou, and Z. Li, “Building task-oriented dialogue systems for online shopping,” in Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), 2017, pp. 4618–4626.

J. Glass, J. Polifroni, S. Seneff, and V. Zue, “Data collection and performance evaluation of spoken dialogue systems: The MIT experience,” in Sixth International Conference on Spoken Language Processing (ICSLP), 2000, pp. 1–4.

M. Gabsdil, “Clarification in spoken dialogue systems,” in Proceedings of the 2003 AAAI Spring Symposium. Workshop on Natural Language Generation in Spoken and Written Dialogue, 2003, pp. 28–35.

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Published

2018-10-31
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