ACO-FFDP in incremental clustering for big data analysis

Abstract

The development of dyamic information analysis, like incremental clustering, is becoming a very important concern in big data. In this paper, we will propose a new incremental clustering algorithm, called "ACO-FFDP-Incremental-Cluster". This algorithm is a combination between "FFDP" a large graph visualization algorithm developed by our team, and "ACO Algorithm". FFDP will set an equilibrium positioning of the large graph; then it will provide the nodes final positions as a vector of coordinates. ACO algorithm will take this vector into consideration and try to find the best clustering configuration possible for new data.