Paper Title
A Comparative Study of Quantum Inspired K-Means Clustering & Classic K-Means Clustering in Signed Social Networks

Abstract
In the era of tremendously increasing social network platforms, massive amount of data is being generated that gives an exciting opportunity to derive relationships among various users sharing the common interest. Also, if social network contains both friends and enemy (signed social networks)then it becomes more challenging to find communities of users sharing the common interests. To address this issue of finding communities in larger signed social networks, quantum inspired k-means clustering is being applied on the real-life signed social networks and results are being compared with classical k-means clustering algorithm. This algorithm is quite helpful in reducing cluster assignment setup at constant cost for every step in classical k-means by the help of quantum phenomena. Keywords - Quantum computing, signed social networks, community, embedding