• ARAS AHMED ALI *College of Information Technology, University College of Goizha- Iraq
  • KANAAN MIKAEL KAKA-KHAN **,***College of Science and Technology, University of Human Development- Iraq
  • ISRAA AL-CHALABI ***College of Natural Science, Sakarya University, Sakarya- Turkey
Keywords: Chatbot, Rule-Based, AIML, Tourist Guide


The tourism industry heavily relies on effective communication, guidance, and assistance to ensure a positive experience for travelers. With the advent of technology, chatbots have emerged as a popular solution for providing aid and direction to tourists. This research paper presents a comprehensive exploration of the design and implementation of a cutting-edge chatbot tailored for tourist guidance, leveraging the power of Artificial Intelligence Markup Language (AIML). The case study focuses on Sulaimani City, wherein a robust dataset comprising 352 meticulously crafted questions and corresponding answers was curated. The developed chatbot model was then seamlessly integrated and deployed on a dedicated test website, enabling real users to interact and engage with it. To gauge the efficacy of the model, a multifaceted evaluation encompassing user satisfaction, accuracy, and response type was conducted. The results unequivocally demonstrate that the AIML-based chatbot surpassed the performance of traditional web-based tourist guides, achieving higher levels of user satisfaction. However, one notable limitation of this research is the use of a small-scale dataset, potentially affecting the chatbot's real-world performance and generalizability. This pioneering research underscores the immense potential of chatbot technology as an indispensable tool for delivering comprehensive and reliable tourist information, thereby revolutionizing the tourism industry.




Download data is not yet available.


S. Zlatanov and J. Popesku, “Current Applications of Artificial Intelligence in Tourism and Hospitality,” no. January, pp. 84–90, 2019, doi: 10.15308/sinteza-2019-84-90.
G. Caldarini, S. Jaf, and K. McGarry, “A Literature Survey of Recent Advances in Chatbots,” Inf., vol. 13, no. 1, 2022, doi: 10.3390/info13010041.
M. das G. Bruno Marietto et al., “Artificial Intelligence Markup Language: A Brief Tutorial,” Int. J. Comput. Sci. Eng. Surv., vol. 4, no. 3, pp. 1–20, 2013, doi: 10.5121/ijcses.2013.4301.
R. Alotaibi, A. Ali, H. Alharthi, and R. Almehamadi, “AI Chatbot for Tourism Recommendations A Case Study in the City of Jeddah, Saudi Arabia,” Int. J. Interact. Mob. Technol., vol. 14, no. 19, pp. 18–30, 2020, doi: 10.3991/ijim.v14i19.17201.
F. Nafis, A. Yahyaouy, and B. Aghoutane, “Chatbots for Cultural Heritage: A Real Added Value,” no. Bml 2021, pp. 502–506, 2022, doi: 10.5220/0010737700003101.
V. Kasinathan, M. H. A. Wahab, S. Z. S. Idrus, A. Mustapha, and K. Z. Yuen, “AIRA Chatbot for Travel: Case Study of AirAsia,” J. Phys. Conf. Ser., vol. 1529, no. 2, 2020, doi: 10.1088/1742-6596/1529/2/022101.
M. Casillo, F. Clarizia, G. D’Aniello, M. De Santo, M. Lombardi, and D. Santaniello, “CHAT-Bot: A cultural heritage aware teller-bot for supporting touristic experiences,” Pattern Recognit. Lett., vol. 131, pp. 234–243, 2020, doi: 10.1016/j.patrec.2020.01.003.
D. S. A. Maylawati et al., “Chatbot for Virtual Travel Assistant with Random Forest and Rapid Automatic Keyword Extraction,” 7th Int. Conf. Comput. Eng. Des. ICCED 2021, 2021, doi: 10.1109/ICCED53389.2021.9664876.
I. Nica, O. A. Tazl, and F. Wotawa, “Chatbot-based tourist recommendations using model-based reasoning,” CEUR Workshop Proc., vol. 2220, pp. 25–30, 2018.
P. Steven, S. Chock, and A. Seeam, “Development of a Smart Tourism Information Chatbot for Mauritius,” pp. 122–130, 2022.
D.-H. Kim, H.-S. Im, J.-H. Hyeon, and J.-W. Jwa, “Development of the Rule-based Smart Tourism Chatbot using Neo4J graph database,” Int. J. Internet, Broadcast. Commun., vol. 13, no. 2, pp. 179–186, 2021, [Online]. Available:
M.-C. Jwa and J.-W. Jwa, “Development of Tourism Information Named Entity Recognition Datasets for the Fine-tune KoBERT-CRF Model,” Int. J. Internet, Broadcast. Commun., vol. 14, no. 2, pp. 55–62, 2022, [Online]. Available:
N. Sripriya, S. Poornima, S. Mohanavalli, R. Pooja Bhaiya, and V. Nikita, “Speech-Based Virtual Travel Assistant for Visually Impaired,” 4th Int. Conf. Comput. Commun. Signal Process. ICCCSP 2020, 2020, doi: 10.1109/ICCCSP49186.2020.9315217.
N. K. Kulkarni and N. Marathe, “Tour Planning Chatbot for Tourism and Travel Industry,” vol. 11, no. 05, pp. 242–246, 2022.
V. Bouras et al., “Chatbots for Cultural Venues: A Topic-Based Approach,” Algorithms, vol. 16, no. 7, 2023, doi: 10.3390/a16070339.
L. Mich and R. Garigliano, “ChatGPT for e-Tourism: a technological perspective,” Inf. Technol. Tour., vol. 25, no. 1, pp. 1–12, 2023, doi: 10.1007/s40558-023-00248-x.
G. Sperlí, “A cultural heritage framework using a Deep Learning based Chatbot for supporting tourist journey,” Expert Syst. Appl., vol. 183, no. May, p. 115277, 2021, doi: 10.1016/j.eswa.2021.115277.
J. Weizenbaum, “ELIZA-A computer program for the study of natural language communication between man and machine,” Commun. ACM, vol. 9, no. 1, pp. 36–45, 1966, doi: 10.1145/365153.365168.
H. yeung Shum, X. dong He, and D. Li, “From Eliza to XiaoIce: challenges and opportunities with social chatbots,” Frontiers of Information Technology and Electronic Engineering, 2018.
“Pandorabots.” (accessed Apr. 12, 2023).
J. Casas, M. O. Tricot, O. Abou Khaled, E. Mugellini, and P. Cudré-Mauroux, “Trends & methods in chatbot evaluation,” ICMI 2020 Companion - Companion Publ. 2020 Int. Conf. Multimodal Interact., no. October, pp. 280–286, 2020, doi: 10.1145/3395035.3425319.
How to Cite