Open Access   Article Go Back

goTripper ChatBot for Tourism

Monalisha Bandyopadhyay1 , Mitali Sahoo2 , Mayur L Rangani3 , Jyoti K Mirji4

Section:Research Paper, Product Type: Journal Paper
Volume-07 , Issue-14 , Page no. 36-40, May-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7si14.3640

Online published on May 15, 2019

Copyright © Monalisha Bandyopadhyay, Mitali Sahoo, Mayur L Rangani, Jyoti K Mirji . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: Monalisha Bandyopadhyay, Mitali Sahoo, Mayur L Rangani, Jyoti K Mirji, “goTripper ChatBot for Tourism,” International Journal of Computer Sciences and Engineering, Vol.07, Issue.14, pp.36-40, 2019.

MLA Style Citation: Monalisha Bandyopadhyay, Mitali Sahoo, Mayur L Rangani, Jyoti K Mirji "goTripper ChatBot for Tourism." International Journal of Computer Sciences and Engineering 07.14 (2019): 36-40.

APA Style Citation: Monalisha Bandyopadhyay, Mitali Sahoo, Mayur L Rangani, Jyoti K Mirji, (2019). goTripper ChatBot for Tourism. International Journal of Computer Sciences and Engineering, 07(14), 36-40.

BibTex Style Citation:
@article{Bandyopadhyay_2019,
author = {Monalisha Bandyopadhyay, Mitali Sahoo, Mayur L Rangani, Jyoti K Mirji},
title = {goTripper ChatBot for Tourism},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2019},
volume = {07},
Issue = {14},
month = {5},
year = {2019},
issn = {2347-2693},
pages = {36-40},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1085},
doi = {https://doi.org/10.26438/ijcse/v7i14.3640}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i14.3640}
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1085
TI - goTripper ChatBot for Tourism
T2 - International Journal of Computer Sciences and Engineering
AU - Monalisha Bandyopadhyay, Mitali Sahoo, Mayur L Rangani, Jyoti K Mirji
PY - 2019
DA - 2019/05/15
PB - IJCSE, Indore, INDIA
SP - 36-40
IS - 14
VL - 07
SN - 2347-2693
ER -

           

Abstract

Tourism is one of the major revenue earners for any country. Many countries growth depends mostly on their tourism industry-generated income. While exploring, many tourists sometimes face some situations where they are not able to reach out other locals of the place for help because there is a problem in the communication or sometimes are majorly not aware of the place. The travellers need to plan their trips well in advance keeping their time and destination in mind. Sometimes, in a hurry, they tend to forget some places for their trip and regret later. This happens when there is no proper planning for the trip. Keeping an eye on all these issues, we introduce goTripper Chatbot. This is an application which is build using OpenNLP (natural language processing) which makes it possible for the bot to understand natural language human text/voice input and initiate further work. It includes technologies like machine learning and artificial intelligence which helps the bot learn of its own and become smart enough to respond back to the user with time. This not only resolves the communication problem people face but also have different features which are required by a tourist when he/she is on their trip. It also provides the user with a scheduled plan of the trip that he/she may follow. Being a ChatBot, it will be easy to use with minimum work efforts required, time efficient and is very economical.

Key-Words / Index Term

ChatBot, tourism, tourists, natural language processing, weather, maps, live chat, OpenNLP, intents, entities

References

[1] Martin C. Brown, “Python: The Complete Reference”, McGraw-Hill Publication, India, pp. 720, 2018.
[2] Sebastian Raschka, “Python Machine Learning”, Packt Publishing Limited; 2nd Revised edition, India, pp. 622, 2017.
[3] Prateek Joshi, “Artificial Intelligence with Python: A Comprehensive Guide to Building Intelligent Apps for Python Beginners and Developers”, Packt Publishing; 1 edition, India, pp. 448, 2017
[4] Christopher M. Bishop, “Pattern Recognition and Machine Learning (Information Science and Statistics)”, Springer; 1st ed. 2006. Corr. 2nd printing 2011 edition, India, pp. 738, 2011
[5] Bhavika R. Ranoliya,” Chatbot for university related FAQs”, In the Proceedings of the 2017 IEEE International Conference, Udupi, India, 2017
[6] Nudtaporn Rosruen,” Chatbot Utilization for Medical Consultant System”, In the Proceedings of the 2018 IEEE International Conference, Bangkok, Thailand, 2019
[7] Ramya Ravi, “Intelligent Chatbot for Easy Web-Analytics Insights”, In the Proceedings of the 2018 IEEE International Conference, Bangalore, India, 2018
[8] Yixuan Chai, “Utterance Censorship of Online Reinforcement Learning Chatbot”, In the Proceedings of the 2018 IEEE International Conference, Volos, Greece, 2018