Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 990

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

An Overview of Chatbot Technology

Open access
Adamopoulou, Eleni, Moussiades, Lefteris·2020·IFIP Advances in Information and Communication Technology
DOI 10.1007/978-3-030-49186-4_31
Open this paper in CoChat — free account

Abstract

The use of chatbots evolved rapidly in numerous fields in recent years, including Marketing, Supporting Systems, Education, Health Care, Cultural Heritage, and Entertainment. In this paper, we first present a historical overview of the evolution of the international community’s interest in chatbots. Next, we discuss the motivations that drive the use of chatbots, and we clarify chatbots’ usefulness in a variety of areas. Moreover, we highlight the impact of social stereotypes on chatbots design. After clarifying necessary technological concepts, we move on to a chatbot classification based on various criteria, such as the area of knowledge they refer to, the need they serve and others. Furthermore, we present the general architecture of modern chatbots while also mentioning the main platforms for their creation. Our engagement with the subject so far, reassures us of the prospects of chatbots and encourages us to study them in greater extent and depth.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1007/978-3-030-49186-4_31

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 4 references

Research works printed but not linked: 26

  1. Bansal, H., Khan, R.: A review paper on human computer interaction. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 8, 53 (2018). https://doi.org/10.23956/ijarcsse.v8i4.630 · DOI
  2. Khanna, A., Pandey, B., Vashishta, K., Kalia, K., Bhale, P., Das, T.: A study of today’s A.I. through chatbots and rediscovery of machine intelligence. Int. J. u- e-Serv. Sci. Technol. 8, 277–284 (2015). https://doi.org/10.14257/ijunesst.2015.8.7.28 · DOI · Paper page
  3. Abu Shawar, B.A., Atwell, E.S.: Chatbots: are they really useful? J. Lang. Technol. Comput. Linguist. 22, 29–49 (2007) · DOI
  4. Klopfenstein, L., Delpriori, S., Malatini, S., Bogliolo, A.: The rise of bots: a survey of conversational interfaces, patterns, and paradigms. In: Proceedings of the 2017 Conference on Designing Interactive Systems, pp. 555–565. Association for Computing Machinery (2017) · DOI
  5. Brandtzaeg, P.B., Følstad, A.: Why people use chatbots. In: Kompatsiaris, I., et al. (eds.) Internet Science, pp. 377–392. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-70284-1_30 · DOI · Paper page
  6. Colby, K.M., Weber, S., Hilf, F.D.: Artificial paranoia. Artif. Intell. 2, 1–25 (1971). https://doi.org/10.1016/0004-3702(71)90002-6 · DOI
  7. Wallace, R.S.: The anatomy of A.L.I.C.E. In: Epstein, R., Roberts, G., Beber, G. (eds.) Parsing the Turing Test: Philosophical and Methodological Issues in the Quest for the Thinking Computer, pp. 181–210. Springer, Cham (2009). https://doi.org/10.1007/978-1-4020-6710-5_13 · DOI
  8. Marietto, M., et al.: Artificial intelligence markup language: a brief tutorial. Int. J. Comput. Sci. Eng. Surv. 4 (2013). https://doi.org/10.5121/ijcses.2013.4301 · DOI
  9. Molnár, G., Zoltán, S.: The role of chatbots in formal education. Presented at the 15 September 2018 · DOI
  10. Colace, F., De Santo, M., Lombardi, M., Pascale, F., Pietrosanto, A., Lemma, S.: Chatbot for e-learning: a case of study. Int. J. Mech. Eng. Robot. Res. 7, 528–533 (2018). https://doi.org/10.18178/ijmerr.7.5.528-533 · DOI
  11. da Costa, P.C.F.: Conversing with personal digital assistants: on gender and artificial intelligence. J. Sci. Technol. Arts 10, 59–72 (2018). https://doi.org/10.7559/citarj.v10i3.563 · DOI
  12. 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, pp. 3506–3510. ACM, New York (2017) · DOI
  13. Følstad, A., Nordheim, C.B., Bjørkli, C.A.: What makes users trust a chatbot for customer service? An exploratory interview study. In: Bodrunova, S.S. (ed.) INSCI 2018. LNCS, vol. 11193, pp. 194–208. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-01437-7_16 · DOI
  14. Sannon, S., Stoll, B., DiFranzo, D., Jung, M., Bazarova, N.N.: How personification and interactivity influence stress-related disclosures to conversational agents. In: Companion of the 2018 ACM Conference on Computer Supported Cooperative Work and Social Computing, pp. 285–288. ACM, New York (2018) · DOI
  15. Dale, R.: The return of the chatbots. Nat. Lang. Eng. 22, 811–817 (2016). https://doi.org/10.1017/S1351324916000243 · DOI · Paper page
  16. Ramesh, K., Ravishankaran, S., Joshi, A., Chandrasekaran, K.: A survey of design techniques for conversational agents. In: Kaushik, S., Gupta, D., Kharb, L., Chahal, D. (eds.) ICICCT 2017. CCIS, vol. 750, pp. 336–350. Springer, Singapore (2017). https://doi.org/10.1007/978-981-10-6544-6_31 · DOI
  17. Akma, N., Hafiz, M., Zainal, A., Fairuz, M., Adnan, Z.: Review of chatbots design techniques. Int. J. Comput. Appl. 181, 7–10 (2018). https://doi.org/10.5120/ijca2018917606 · DOI
  18. An e-business chatbot using AIML and LSA - Semantic Scholar. https://www.semanticscholar.org/paper/An-e-business-chatbot-using-AIML-and-LSA-Thomas/906c91ca389a29b47a0ec072d54e23ddaa757c88
  19. Jung, S.: Semantic vector learning for natural language understanding. Comput. Speech Lang. 56, 130–145 (2019). https://doi.org/10.1016/j.csl.2018.12.008 · DOI
  20. Nimavat, K., Champaneria, T.: Chatbots: an overview types, architecture, tools and future possibilities. Int. J. Sci. Res. Dev. 5, 1019–1024 (2017)
  21. Kucherbaev, P., Bozzon, A., Houben, G.-J.: Human-aided bots. IEEE Internet Comput. 22, 36–43 (2018). https://doi.org/10.1109/MIC.2018.252095348 · DOI
  22. Hien, H.T., Cuong, P.-N., Nam, L.N.H., Nhung, H.L.T.K., Thang, L.D.: Intelligent assistants in higher-education environments: the FIT-EBot, a chatbot for administrative and learning support. In: Proceedings of the Ninth International Symposium on Information and Communication Technology, pp. 69–76. ACM, New York (2018) · DOI
  23. Wu, Y., Wu, W., Xing, C., Zhou, M., Li, Z.: Sequential Matching Network: A New Architecture for Multi-turn Response Selection in Retrieval-based Chatbots. arXiv:1612.01627 [cs] (2016) · DOI
  24. Augello, A., Gentile, M., Dignum, F.: An overview of open-source chatbots social skills. In: Diplaris, S., Satsiou, A., Følstad, A., Vafopoulos, M., Vilarinho, T. (eds.) INSCI 2017. LNCS, vol. 10750, pp. 236–248. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-77547-0_18 · DOI
  25. Zumstein, D., Hundertmark, S.: Chatbots – an interactive technology for personalized communication, transactions and services. IADIS Int. J. WWW/Internet 15, 96–109 (2017)
  26. Singh, S., Darbari, H., Bhattacharjee, K., Verma, S.: Open source NLG systems: a survey with a vision to design a true NLG system. 9, 4409–4421 (2016)

Cited by

See all 990

Metadata

Authors
Adamopoulou, E., & Moussiades, L.
Venue
IFIP Advances in Information and Communication Technology
Publisher
Springer International Publishing
Published
2020
Pages
373-383
ISSN
  • 1868-422X (ISSN-L)
  • 1868-4238
DOI
10.1007/978-3-030-49186-4_31
OpenAlex
W3028999579
Cited by
990
References
4
FWCI
42.43
Type
conference paper
Language
en
Open access
green
Licence

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: An Overview of Chatbot Technology. https://app.cochat.ai/papers/10.1007/978-3-030-49186-4_31
The paper
Adamopoulou, E., & Moussiades, L. (2020). An Overview of Chatbot Technology. IFIP Advances in Information and Communication Technology. https://doi.org/10.1007/978-3-030-49186-4_31

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.