Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Hand Gesture Controller for Robotic-Wheelchair Using Microelectromechanical Sensor ADXL 345 Read chapter Read first chapter

2019 | OriginalPaper | Chapter

AIML and Sequence-to-Sequence Models to Build Artificial Intelligence Chatbots: Insights from a Comparative Analysis

Authors : Nishant Teckchandani, Aditya Santokhee, Girish Bekaroo

Published in: Smart and Sustainable Engineering for Next Generation Applications

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

A chatbot is a software that is able to autonomously communicate with a human being through text and due to its usefulness, an increasing number of businesses are implementing such tools in order to provide timely communication to their clients. In the past, whilst literature has focused on implementing innovative chatbots and the evaluation of such tools, limited studies have been done to critically comparing such conversational systems. In order to address this gap, this study critically compares the Artificial Intelligence Mark-up Language (AIML), and Sequence-to-Sequence models for building chatbots. In this endeavor, two chatbots were developed to implement each model and were evaluated using a mixture of glass box and black box evaluation, based on 3 metrics, namely, user’s satisfaction, the information retrieval rate, and the task completion rate of each chatbot. Results showed that the AIML chatbot ensured better user satisfaction, and task completion rate, while the Sequence-to-Sequence model had better information retrieval rate.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter A Machine Learning Model to Predict the Performance of University Students
next chapter Accurate Footprint Satellite Positioning Space System
Literature
1.
Levy, M.: Technologies in use for second language learning. Mod. Lang. J. 93(1), 769–782 (2009)CrossRef
2.
Madhu, D., Jain, C., Sebastain, E., Shaji, S., Ajayakumar, A.: A novel approach for medical assistance using trained chatbot. In: 2017 International Conference on Inventive Communication and Computational Technologies (ICICCT) (2017)
3.
4.
Shawar, B., Atwell, E.: Different measurements metrics to evaluate a chatbot system. In: Proceedings of the Workshop on Bridging the Gap: Academic and Industrial Research in Dialog Technologies (2007)
5.
Qiu, M., Li, F., 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 (2017)
6.
Serban, I., Sordoni, A., Bengio, Y., Courville, A., Pineau, J.: Building end-to-end dialogue systems using generative hierarchical neural network models. In: AAAI (2016)
7.
8.
Xu, A., Liu, Z., Guo, Y., Sinha, V., Akkiraju, R.: A new chatbot for customer service on social media. In: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (2017)
9.
Sutskever, I., Vinyals, O., Le, Q.: Sequence to sequence learning with neural networks. In: Advances in Neural Information Processing Systems (2014)
10.
Satu, M., Parvez, M.: Review of integrated applications with AIML based chatbot. In: 2015 1st International Conference on Computer and Information Engineering (ICCIE) (2015)
11.
Masche, J., Le, N.: A review of technologies for conversational systems. In: International Conference on Computer Science, Applied Mathematics and Applications (2017)
12.
13.
Shawar, B., Atwell, E.: A comparison between ALICE and Elizabeth chatbot systems. University of Leeds, School of Computing research report 2002, Leeds (2002)
14.
15.
Radziwill, N., Benton, M.: Evaluating quality of chatbots and intelligent conversational agents. Softw. Qual. Prof. 19(3), 25–36 (2017)
16.
17.
Shieber, S.: Lessons from a restricted Turing test. Communication 37(6), 70–78 (1994)
18.
Price, P.: Evaluation of spoken language systems: the ATIS domain. In: Speech and Natural Language: Proceedings of a Workshop Held at Hidden Valley, Pennsylvania (1990)
19.
Maier, E., Mast, M., LuperFoy, S.: Dialogue processing in spoken language systems. In: DPSLS: Workshop on Dialogue Processing in Spoken Language Systems (1996)
20.
Papineni, K., Roukos, S., Ward, T., Zhu, W.: BLEU: a method for automatic evaluation of machine translation. In: Proceedings of the 40th Annual Meeting on Association for Computational Linguistics (2002)
21.
Liu, C., Lowe, R., Serban, I., Noseworthy, M., Charlin, L., Pineau, J.: How NOT to evaluate your dialogue system: an empirical study of unsupervised evaluation metrics for dialogue response generation. In: Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (2016)
22.
Zhang, X., He, S., Song, X., Wei, P., Jiang, S., Ye, Q., Jiao, J., Lau, R.: Keyword-driven image captioning via context-dependent bilateral LSTM. In: 2017 IEEE International Conference on Multimedia and Expo (ICME) (2017)
Metadata
Title
AIML and Sequence-to-Sequence Models to Build Artificial Intelligence Chatbots: Insights from a Comparative Analysis
Authors
Nishant Teckchandani
Aditya Santokhee
Girish Bekaroo
Copyright Year
2019
Book
Smart and Sustainable Engineering for Next Generation Applications

Print ISBN: 978-3-030-18239-7

Electronic ISBN: 978-3-030-18240-3

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-18240-3_30