Efficient Scheme to Improve Top-k Position Monitoring of Document Stream
The efficient processing of document streams have been still research area in many information filtering system with lots of algorithms to design the efficient document stream monitoring system. This paper proposes a “K-Nearest Neigbors (K-NN) Clustering” framework. The proposed framework is used to reduces the recomputational and memory utilization. The main goal of this method is to simply seperate the data based on the assumed similarties between various classes. hence, the classes can be differentiated from one another by searching for similarities between the data provided. It helps to give better throughput and less overhead. Keywords - Top-k Query, Document Stream, Streaming Text Data, Feature Selection.