The International Journal of Innovative Research in Computer and Communication Engineering
Data stream mining is become new emerging topic for research in knowledge discovery. In this continuous changing nature of data creates problem in mining the knowledge from it and its difficult to store. There are some techniques and algorithms which are using for mining in the data stream like classification, clustering and frequent patterns. Here gives an overview of all these techniques with their merits and demerits. There are mainly four challenges termed as concept drift, infinite length, concept evaluation and limited labeled data.