• Shreyas Yeola Student,Computer Engg,G.S.Moze C.O.E.,Balewadi,Pune.
  • Akshay Wakhare Student,Computer Engg,G.S.Moze C.O.E.,Balewadi,Pune.
  • Swapnil Mule Student,Computer Engg,G.S.Moze C.O.E.,Balewadi,Pune.
  • Shrinivas Halahalli professor,Computer Engg,G.S.Moze C.O.E.,Balewadi,Pune.


Activity bag,Social graph,text mining


Friend Recommendation using LDA Algorithm” is a novel semantic-based friend recommendation system for social networks,recommends friends to users based on their activity bag instead of social graphs. Existing social networking services recommend friends to users based on their social graphs, which may not be the most appropriate to reflect a user’s preferences on friend selection in real life. Inspired by text mining, we model a user’s daily life as life documents, from which his/her life styles are extracted by using the Latent Dirichlet Allocation algorithm. We further propose a similarity metric to measure the similarity of life styles between users, and calculate users’ impact in terms of life styles with a friend-matching graph.So,our system integrates a feedback mechanism to further improve the recommendation accuracy. This system will be used on the Android-based smartphones.


“Friendbook: a semantic based friend recommendation system for social networks.”

Zhibo Wang, Student Member, IEEE, Jilong Liao, Qing Cao, Member, IEEE, Hairong Qi, Senior Member, IEEE, and Zhi Wang, Member.


Facebook statistics.


Rotten tomatoes.

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Additional Files



How to Cite

Shreyas Yeola, Akshay Wakhare, Swapnil Mule, & Shrinivas Halahalli. (2016). FRIEND RECOMMENDATION USING LDA ALGORITHM. International Education and Research Journal (IERJ), 2(1). Retrieved from