Clustering Algorithm for Ubiquitous Data Stream Mining Based on Slip Window
Recently, ubiquitous Data Stream Mining has become a new focus of data mining gradually. For its having finite ubiquitous resource mine infinite data stream and returning outcome anytime and anywhere,this paper suggest stream clustering algorithm based on slip window. It divides a window into n average units, on which the increasable and knowledge-correlated mining is executed based, so as to heighten its efficiency. As window is to slip,algorithm weaken the first unit's outcome of current window with weakened function and eliminate its affect for current outcome so as to make true the next increasable mining in next window.