Friend recommendation system based on lifestyles of users
Tofik R. Kacchi, Anil V. Deorankar · 2016
Due to the increasing exponential growth in the use of social networking services, different social networking services have provided us new radical ways of making friends. Different recommendation system exist which are classified into two top level categories as object recommendation and link recommendation. In this paper, our focus will be on later one. The proposed system will work like a client-server application where the user which is requesting the query act as a client. Life documents of each user are collected from the client with the help of browser. In this phase, these collected data will be stored into a file either in semi-structured or structured format accordingly. The life styles of users are extracted by using either hadoop technology or SQL depending on the type of file as input to it. Then the concept of reverse indexing is used for easy retrieval of the desired data. Then with the help of graph data structure we can represent the relationship between users. As recommendation is based on different priorities like similar interest, similar blood group, nearby location, ranking is also one of the factor. So, the ranks of users are calculated using the pseudocode mentioned in this paper. Finally, client/user sends a query and server will respond a list of friends to the user/client (browser) accordingly.