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Tourist Place Recommendation System using Social Networking Data

Author(s):

Akshay Babhulkar , D y patil college of engineering; Ganesh Mandade, d y patil coe; Sudarshan Hadapkar, d y patil coe; Neelkamal Bhandari, d y patil coe; Trupti Phutane, d y patil coe

Keywords:

Tourist data, User based Collaborative Filtering, Item based Collaborative Filtering, SVM, Facebook and Twitter API

Abstract

Recommender system using social networks to promote smart tourism Latest revolution in computing areas such as communication involving networks of people (social networks), intelligent devices, smart mobile computing, and communication devices that will form cyber-physical social systems. So can we make best use of this enormous data sources to proactively recommend different items to users, based on user context. This category of recommendation systems is Push recommendations. We are trying to propose a recommender model, which shall use implicit, local and personal information of the user from the Internet of Things, Social Account, user web browsing history, smart devices etc. where anything will be connected any time. This proposed system shall be pushed to the user, and not of only 1 type. This can be used by the end users to avail the facilities and services, but for which users has to register and Travel and Tour companies will register and upload the services and facilities they offer. So this system can provide vendors new opportunities to get new business and consumers can avail the services and facilities.

Other Details

Paper ID: IJSRDV6I40236
Published in: Volume : 6, Issue : 4
Publication Date: 01/07/2018
Page(s): 161-166

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