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@article{152160,
        author = {Nandarani Kadam and Sarika Solanke},
        title = {TravelBot: Utilizing social media dialogue for Travel Recommendation},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {2},
        pages = {563-568},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=152160},
        abstract = {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.},
        keywords = {Artificial Intelligence, Chatbot, Machine
Learning, Natural language processing, Travel, Twitter.
},
        month = {},
        }