Friend Recommendation in Online Social Networks using LDA
Author(s):
M.Kanchana , Professor, Department of Information Technology, Karpaga Vinayaga College of Engineering & Technology, Chinna Kolambakkam, Madurantakam Taluk, Kanchipuram-603308, Tamil Nadu, India; S.P.Adaikkammai, Karpaga Vinayaga College of Engineering & Technology; V.Amirtham, Karpaga Vinayaga College of Engineering & TechnologyKeywords:
Fluorescent Microscope Image, Adaptive SegmentationAbstract:
Existing social network services provide list of friends to users based on their request given. But it will not fulfil the user’s preferences in real life. Due to overloaded memory of the server memory size increases and lacking its efficiency. By implementing the Latent Dirichlet Allocation Algorithm we extracting their lifestyles and sensing the similarity of lifestyles between users by using embedded sensors in the smartphones. Based on friend matching graphs we return a list of people with highest similarity of lifestyles. Feedback mechanism is integrated in this friendbook to get the results of users in choosing friends. We have implemented friendbook on the Android-based smartphones and evaluated its performance on both small scale experiments and large scale simulations. Finally, we reduce the memory size of the server and improving its performance.
Other Details:
| Manuscript Id | : | J4RV1I1033 |
| Published in | : | Volume : 1, Issue : 1 |
| Publication Date | : | 01/04/2015 |
| Page(s) | : | 7-10 |
