ProgramsView all programs
From the news
- Chancellor Amma Addresses the Parliament of World’s Religions
- Amrita Students Qualify for the European Mars Rover Challenge
Publication Type : Book Chapter
Publisher : Advances in Intelligent Systems and Computing.
Source : Advances in Intelligent Systems and Computing, Volume 398, p.601 - 614 (2016)
ISBN : 9788132226727
Campus : Coimbatore
School : School of Engineering
Center : Center for Computational Engineering and Networking
Department : Computer Science
Verified : Yes
Year : 2016
Abstract : In today’s world, social networking sites are becoming increasingly popular. Often we find suggestions for friends, from such social networking sites. These friend suggestions help us identify friends that we may have lost touch with or new friends that we may want to make. At the same time, these friend suggestions may not be that accurate. To recommend a friend, social networking sites collect information about user’s social circle and then build a social network based on this information. This network is then used to recommend to a user, the people he might want to befriend. FoF algorithm is one of the traditional techniques used to recommend friends in a social network. Delta-SimRank is an algorithm used to compute the similarity between objects in a network. This algorithm is also applied on a social network to determine the similarity between users. Here, we evaluate Delta-SimRank and FoF algorithm in terms of the friend suggestion provided by them, when applied on a Facebook dataset. It is observed that Delta-SimRank provides a higher precise similarity score because it considers the entire network around a user.
Cite this Research Publication : A. Ravindran, Kumar, P. N., and Subathra P., “Similarity Scores Evaluation in Social Networking Sites”, in Advances in Intelligent Systems and Computing, vol. 398, 2016, pp. 601 - 614.