Critical Analysis of Conversational Agent Technology for Intelligent Customer Support and Proposition of a New Solution
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Trends with conversational agents outside the education sector tend to focus more on leveraging machine learning techniques, neural networks, IoT, and advanced APIs.
“the trends with conversational agents outside of the education sector tend to have more focus on leveraging machine learning techniques, utilising cutting edge technological concepts such as neural networks, internet of things (IoT) and advanced API's to create more powerful and advanced conversational agents”
From Pedagogical AI conversational agents in higher education: a conceptual framework and survey of the state of the art (2025) · cites this paper as Modrzejewski & Rokita, 2018
Cites
Thumbs up?: sentiment classification using machine learning techniques
Pang, B., Lee, L., & Vaithyanathan, S. (2002) · Proceedings of the ACL-02 conference on Empirical methods in natural language processing - EMNLP '02 · doi:10.3115/1118693.1118704 · Cited by 7,024 · see citing works
ELIZA—a computer program for the study of natural language communication between man and machine
Weizenbaum, J. (1966) · Communications of the ACM · doi:10.1145/365153.365168 · Cited by 4,452 · see citing works
ELIZA — a computer program for the study of natural language communication between man and machine
Weizenbaum, J. (1983) · Communications of the ACM · doi:10.1145/357980.357991 · Cited by 2,765 · see citing works
Survey on Chatbot Design Techniques in Speech Conversation Systems
A., S., & John, D. (2015) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2015.060712 · Cited by 479 · see citing works
New Directions In Question Answering
Maybury, M. T. (2006) · Text, speech and language technology · doi:10.1007/978-1-4020-4746-6_18 · Cited by 161 · see citing works
Chatbot Using a Knowledge in Database: Human-to-Machine Conversation Modeling
Setiaji, B., & Wibowo, F. W. (2016) · International Conference on Intelligent Systems, Modelling and Simulation · doi:10.1109/isms.2016.53 · Cited by 134 · see citing works
OntBot: Ontology based chatbot
Al-Zubaide, H., & Issa, A. A. (2011) · doi:10.1109/isiict.2011.6149594 · Cited by 113 · see citing works
Design and Implementation of Conversational Agents for Harvesting Feedback in eLearning Systems
Lundqvist, K. Ø., Pursey, G., & Williams, S. A. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-40814-4_79 · Cited by 18 · see citing works
Flagged first, then by citations
- Authors
- Modrzejewski, M., & Rokita, P.
- Affiliations
- Warsaw University of Technology (PL)
- Corresponding author
- Modrzejewski, Mateusz
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2018
- Pages
- 723-733
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2802191603
- Cited by
- 1
- References
- 8
- Citations by year
- 2025: 1
- FWCI
- 0.00
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- chatbots, intelligent customer service, customer service efficiency, human-machine interaction, knowledge engineering, natural language processing
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
