Paper Title

Location based Friend Recommendation System

Authors

Abhishek Sable

Keywords

Friend recommendation, collaborative filtering, social network, Recommendation system.

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.

How To Cite

"Location based Friend Recommendation System", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.4, Issue 7, page no.460 - 464, July-2019, Available :https://ijsdr.org/papers/IJSDR1907079.pdf

Issue

Volume 4 Issue 7, July-2019

Pages : 460 - 464

Other Publication Details

Paper Reg. ID: IJSDR_190868

Published Paper Id: IJSDR1907079

Downloads: 000347168

Research Area: Engineering

Country: Indore, MadhyaPradesh, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR1907079

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR1907079

About Publisher

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

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