Skip to main content
SpringerLink
Log in

A Survey on Conversational Agents/Chatbots Classification and Design Techniques

  • Conference paper
  • First Online:
Book cover Web, Artificial Intelligence and Network Applications (WAINA 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 927))

Abstract

A chatbot can be defined as a computer program, designed to interact with users using natural language or text in a way that the user thinks he is having dialogue with a human. Most of the chatbots utilise the algorithms of artificial intelligence (AI) in order to generate required response. Earlier chatbots merely created an illusion of intelligence by employing much simpler pattern matching and string processing design techniques for their interaction with users using rule-based and generative-based models. However, with the emergence of new technologies more intelligent systems have emerged using complex knowledge-based models. This paper aims to discuss chatbots classification, their design techniques used in earlier and modern chatbots and how the two main categories of chatbots handle conversation context.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Zadrozny, W., et al.: Natural language dialogue for personalized interaction. Commun. ACM 43(8), 116–120 (2000)

    Article  Google Scholar 

  2. Hussain, S., Athula, G.: Extending a conventional chatbot knowledge base to external knowledge source and introducing user based sessions for diabetes education. In: 2018 32nd International Conference on Advanced Information Networking and Applications Workshops (WAINA) 2018. IEEE

    Google Scholar 

  3. Levesque, H.J.: Common sense, the turing test, and the quest for real AI: Reflections on Natural and Artificial Intelligence. MIT Press, Cambridge (2017)

    Google Scholar 

  4. Wikipedia: Chatbot. 29 December 2018 (cited 30 December 2018). https://en.wikipedia.org/wiki/Chatbot

  5. Weizenbaum, J.: ELIZA–a computer program for the study of natural language communication between man and machine. Commun. ACM 26(1), 23–28 (1983)

    Article  Google Scholar 

  6. Wikipedia. Artificial Linguistic Internet Computer Entity. 19 November 2018 (cited 30 December 2018). https://en.wikipedia.org/wiki/Artificial_Linguistic_Internet_Computer_Entity

  7. Wallace, R.S.: The anatomy of ALICE. In: Parsing the Turing Test, pp. 181–210. Springer, Dordrecht (2009)

    Google Scholar 

  8. Ramesh, K., et al.: A Survey of Design Techniques for Conversational Agents. In: International Conference on Information, Communication and Computing Technology. Springer, Singapore (2017)

    Google Scholar 

  9. Budulan, S.: Chatbot Categories and Their Limitations (2018). (cited May 2018). https://dzone.com/articles/chatbots-categories-and-their-limitations-1

  10. Chen, H., et al.: A Survey on Dialogue Systems: Recent Advances and New Frontiers (2017). arXiv preprint arXiv:1711.01731

  11. Yan, Z., et al.: Building Task-Oriented Dialogue Systems for Online Shopping. In: AAAI (2017)

    Google Scholar 

  12. Masche, J., Le, N.-T.: A Review of Technologies for Conversational Systems. In: International Conference on Computer Science, Applied Mathematics and Applications. Springer, Cham (2017)

    Google Scholar 

  13. Abdul-Kader, S.A., Woods, J.: Survey on chatbot design techniques in speech conversation systems. Int. J. Adv. Comput. Sci. Appl. 6(7), 72–80 (2015)

    Google Scholar 

  14. Mathur, V., Singh, A.: The Rapidly Changing Landscape of Conversational Agents (2018). arXiv preprint arXiv:1803.08419

  15. Bradeško, L., Mladenić, D.: A survey of chatbot systems through a loebner prize competition. In: Proceedings of Slovenian Language Technologies Society Eighth Conference of Language Technologies (2012)

    Google Scholar 

  16. Weizenbaum, J.: ELIZA—a computer program for the study of natural language communication between man and machine. Commun. ACM 9(1), 36–45 (1966)

    Article  Google Scholar 

  17. Clarke, D.: Three AI Technologies that could make chatbots intelligent. 24 March 2018 (cited 18 December 2018). https://hackernoon.com/three-ai-technologies-that-could-make-chatbots-intelligent-10f8c6e8b4b0

  18. Shawar, B.A., Atwell, E.: Chatbots: are they really useful? Zeitschrift für Computerlinguistik und Sprachtechnologie, p. 29 (2007)

    Google Scholar 

  19. Wikipedia contributors. ChatScript. Wikipedia, The Free Encyclopedia. 4 September 2018, 19:19 UTC. https://en.wikipedia.org/w/index.php?title=ChatScript&oldid=858055386. Accessed 22 Jan 2019

  20. Robino, G.: How to build your first chatbot using Chatscript (2018). (cited 18 December 2018). https://medium.freecodecamp.org/chatscript-for-beginners-chatbots-developers-c58bb591da8

  21. Milward, D., Beveridge, M.: Ontology-based dialogue systems. In: Proceedings of 3rd Workshop on Knowledge and reasoning in practical dialogue systems (IJCAI 2003) 2003

    Google Scholar 

  22. Al-Zubaide, H., Issa, A.A.: Ontbot: Ontology based chatbot. In: 2011 Fourth International Symposium on Innovation in Information & Communication Technology (ISIICT). IEEE (2011)

    Google Scholar 

  23. Nuez Ezquerra, A.: Implementing ChatBots using Neural Machine Translation Techniques (2018). Universitat Politècnica de Catalunya

    Google Scholar 

  24. Csáky, R.: Deep Learning Based Chatbot Models (2017). https://doi.org/10.13140/rg.2.2.21857.40801

  25. Pelk, H.: Machine learning, neural networks and algorithms (2016). (cited 18 January 2019). https://itnext.io/machine-learning-neural-networks-and-algorithms-4cd27a105b89

  26. Wikipedia contributors. Artificial neural network. In: Wikipedia, The Free Encyclopedia. https://en.wikipedia.org/w/index.php?title=Artificial_neural_network&oldid=878429976. Accessed 13:24, 25 Jan 2019

  27. Young, T., et al.: Recent trends in deep learning based natural language processing. IEEE Comput. Intell. Mag. 13(3), 55–75 (2018)

    Article  Google Scholar 

  28. Cahn, J.: CHATBOT: Architecture, design, and development. In: University of Pennsylvania School of Engineering and Applied Science Department of Computer and Information Science (2017)

    Google Scholar 

  29. Cho, K., et al.: Learning phrase representations using RNN encoder-decoder for statistical machine translation (2014). arXiv preprint arXiv:1406.1078

  30. Sak, H., Senior, A., Beaufays, F.: Long short-term memory recurrent neural network architectures for large scale acoustic modeling. In: Fifteenth Annual Conference of the International Speech Communication Association (2014)

    Google Scholar 

  31. Ji, Z., et al.: An information retrieval approach to short text conversation (2014). arXiv preprint. arXiv:1408.6988.1

    Google Scholar 

  32. Duijst, D., Sandberg, J., Buzzo, D.: Can we Improve the User Experience of Chatbots with Personalisation? (2017)

    Google Scholar 

  33. Liu, B., Xu, Z., Sun, C., Wang, B., Wang, X., Wong, D.F., Zhang, M.: Content-oriented user modeling for personalized response ranking in Chatbots. IEEE/ACM Trans. Audio Speech Lang. Process. (2018)

    Google Scholar 

  34. Pilato, G., Augello, A., Gaglio, S.: A modular architecture for adaptive ChatBots. In: Proceedings of 5th IEEE International Conference on Semantic Computing, ICSC 2011 (2011)

    Google Scholar 

  35. Vtyurina, A., Savenkov, D., Agichtein, E., Clarke, C.L.A.: Exploring conversational search with humans, assistants, and wizards. In: Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems – CHI EA 2017 (2017)

    Google Scholar 

  36. Niculescu, A.I., Banchs, R.E.: Strategies to cope with errors in human-machine spoken interactions: using chatbots as back-off mechanism for task-oriented dialogues. In: Errors by Humans Mach. multimedia, multimodal Multiling, Data Process (2015)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. College of Engineering and Science, Victoria University Sydney, Sydney, Australia

    Shafquat Hussain, Omid Ameri Sianaki & Nedal Ababneh

Authors
  1. Shafquat Hussain
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Omid Ameri Sianaki
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nedal Ababneh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shafquat Hussain .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Department of Advanced Sciences, Hosei University, Koganei-Shi, Tokyo, Japan

    Makoto Takizawa

  3. Department of Computer Science, Technical University of Catalonia, Barcelona, Barcelona, Spain

    Fatos Xhafa

  4. Faculty of Business Administration, Rissho University, Tokyo, Japan

    Tomoya Enokido

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Hussain, S., Ameri Sianaki, O., Ababneh, N. (2019). A Survey on Conversational Agents/Chatbots Classification and Design Techniques. In: Barolli, L., Takizawa, M., Xhafa, F., Enokido, T. (eds) Web, Artificial Intelligence and Network Applications. WAINA 2019. Advances in Intelligent Systems and Computing, vol 927. Springer, Cham. https://doi.org/10.1007/978-3-030-15035-8_93

Download citation

Publish with us

Policies and ethics

Search

Navigation