Downloads: 113 | Views: 297
Survey Paper | Computer Science & Engineering | India | Volume 4 Issue 10, October 2015 | Popularity: 6.8 / 10
A Survey Paper on FriendFinder: A Lifestyle based Friend Recommender App for Smart Phone Users
Chinar Bhandari, Asst Prof. M.D Ingle
Abstract: Todays Social Networking services focuses towards suggesting you friends based on users social graph or Geo-location based, which neither take users life style into account or users liking, disliking etc. Suggesting friends based on social graphs may not be the best preference for the users. In this paper, we present FriendFinder, a novel semantic-based friend suggesting system which suggest friends to users based on their life style and daily curricular activities on mobile phone instead of social graphs. FriendFinder captures users data i. e. daily activities and work done through mobile, for ex - App Usage, App Frequency, Browser Activities etc. Then we create a user profile with all gathered data and find most relevant matching profiles of existing candidate friends matching our profile for similarity and suggesting the result out of similarity test to the user as a friend.
Keywords: Friend recommendation, mobile sensing, life style, social networks, app usage, app frequency, browser activities, categories
Edition: Volume 4 Issue 10, October 2015
Pages: 1356 - 1358
Make Sure to Disable the Pop-Up Blocker of Web Browser
Similar Articles
Downloads: 101
Review Papers, Computer Science & Engineering, India, Volume 3 Issue 11, November 2014
Pages: 747 - 749A Survey of Friendbook Recommendation Services
Pankaj L. Pingate, S. M. Rokade
Downloads: 108 | Weekly Hits: ⮙1 | Monthly Hits: ⮙1
M.Tech / M.E / PhD Thesis, Computer Science & Engineering, India, Volume 5 Issue 1, January 2016
Pages: 1156 - 1161Social Network Friend Recommendation System Using Semantic Web
Pankaj Pingate, S. M. Rokade
Downloads: 111
Research Paper, Computer Science & Engineering, India, Volume 4 Issue 11, November 2015
Pages: 1699 - 1701FriendBook+: An Activity Based Friend Recommendation System for Social Networks
Bhavya.K
Downloads: 111
M.Tech / M.E / PhD Thesis, Computer Science & Engineering, India, Volume 4 Issue 12, December 2015
Pages: 1458 - 1462Recommending Friends on Social Network with Artificial Intelligence Approach
Akram Shaikh, Sandeep Khanna
Downloads: 114
Research Paper, Computer Science & Engineering, India, Volume 5 Issue 3, March 2016
Pages: 2169 - 2172Prediction of Bone Loss Rate Based on Oesteoporosis Risk Features
M. Saranya, Dr. K.Sarojini