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ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
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Volume 7 | Issue 8

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Paper Title: Location based Friend Recommendation System
Authors Name: Abhishek Sable
Unique Id: IJSDR1907079
Published In: Volume 4 Issue 7, July-2019
Abstract: Friend recommendation is one of the most popular characteristics of social network platforms, which recommends familiar people to users. The concept of friend recommendation originates from social networks such as Twitter & facebook, which uses friends-of-friend method to recommend people. We can say users do not make friends from random people but end up making friends with their friends’ friends. The existing methods have narrow scope of recommendation and are less efficient. We put forward a new friend recommendation model to overpower the defects of existing system. For better friend recommendation system with high accuracy, we will use collaborative filtering method to compare similar, dissimilar data of users and will make a recommendation system which gives user to user recommendation based on their similar choices, activities and preferences. Location based friend recommendation system are becoming popular because it brings physical world to digital platform and gives better insight of user’s preferences or interest This recommendation system will increase the scope of recommendation from one user to other with similar set of interest and their location.
Keywords: Friend recommendation, collaborative filtering, social network, Recommendation system.
Cite Article: "Location based Friend Recommendation System", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.4, Issue 7, page no.460 - 464, July-2019, Available :http://www.ijsdr.org/papers/IJSDR1907079.pdf
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Publication Details: Published Paper ID: IJSDR1907079
Registration ID:190868
Published In: Volume 4 Issue 7, July-2019
DOI (Digital Object Identifier):
Page No: 460 - 464
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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