TravelBot: Utilizing social media dialogue for Travel Recommendation
Nandarani Kadam, Sarika Solanke
Artificial Intelligence, Chatbot, Machine Learning, Natural language processing, Travel, Twitter.
Use of social media in tourism is increasing rapidly. Due to increasing Internet usage, many businesses now use online platforms to handle customer inquiries, and many of them turn to chatbots for improving their customer service. Travelbot is a chatbot; a computer application that interacts with users using natural language in a similar way to imitate a human travel agent. Travelbot is using twitter data for recommending countries to users for travel. The travelbot uses tweepy api and perform filtering on data to get all travel related tweets. When travelbot recommended countries to travel realized that there are number of features available like safety, quality of life, healthcare etc. So all these features are important? To solve this question need to use classification algorithm. First Decision tree algorithm is used with these datasets, on the values of feature importance got accuracy score 48.39%. Then Random Forest Algorithm is used with these datasets, on the values of feature importance got accuracy score 78.65%. According to these values we can see the accuracy of random forest is increased 30% as compare to decision tree algorithm.
Article Details
Unique Paper ID: 152160

Publication Volume & Issue: Volume 8, Issue 2

Page(s): 563 - 568
Article Preview & Download

Share This Article

Conference Alert


AICTE Sponsored National Conference on Smart Systems and Technologies

Last Date: 25th November 2021

SWEC- Management


Last Date: 7th November 2021

Go To Issue

Call For Paper

Volume 9 Issue 10

Last Date for paper submitting for March Issue is 25 March 2023

About Us enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on

Social Media

Google Verified Reviews

Contact Details