HYBRID RECOMMENDER SYSTEM FOR TOURISM BASED ON BIG DATA AND AI:A CONCEPTUAL FRAMEWORK

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Upadrasta Deepika
Assistant Professor, Department of Electronics and Communication Engineering, Sridevi Women’s Engineering College, Hyderabad, India, deepika.upadrasta@gmail.com

Priyanka.G
U. G Student, Department of Electronics and communication Engineering, Sridevi Women’s Engineering College, Hyderabad, India

Lavanya.k
U. G Student, Department of Electronics and communication Engineering, Sridevi Women’s Engineering College, Hyderabad, India

Saba
U. G Student, Department of Electronics and communication Engineering, Sridevi Women’s Engineering College, Hyderabad, India

Vol 17, No 07 ( 2022 )   |  DOI: 10.5281/zenodo.6879706   |   Licensing: CC 4.0   |   Pg no: 266-273   |   Published on: 25-07-2022

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Abstract
Nowadays due to development of the internet a lot of things has changed in the world. The tourism recommenter system gives the aim to develop a personalized travel planning system that simultaneously considers all categories of user requirements and provides users with a travel schedule planning service. This will enable the user in finding what they are looking for, easily without spending time and effort. In this project we have to build recommender system which recommends tourist travel locations based on his previous rated venues. Recommended enginr is build on an observation that tourist always try to explore places which are nearby first. Let’s consider an for simplifying things. Bob arrived in Toronto and wants to visit top places in Toronto, If h starts exploring a particular neighborhood, he wants to finish exploring all good places in that neighbourhood before moving to other neighborhood. Keeping this in mind we have to recommend tourist a neighborhood, with venues where he can visit. We will be using location data to get best spots in neighbourhood. The project provides a travel itinerary for users using their travel details like destination, budget ,start and end dates of travel and their preferences of attraction categories, hotel amenities and cuisine type. Our project significantly reduces the time spent on planning for a satisfactory vacation. Hindi proposed system a recommender system is based on big data technologies, artificial intelligence

Keywords:
recommender system ; user profiling content-based filtering ; collaborative filtering ; hybrid recommender system ; e-tourism ; trip planning

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