Abstract: In the field of data mining, data streams play an important role. In order to make intelligent use of data streams, first we need to handle them properly. The notation data stream itself represents the nature of such data. They possess the property of being dynamic and continuous in nature. That is the data keeps on changing the features and properties with time. Due to the above mentioned properties of data streams, various challenges are posed by them to researchers. These challenges are infinite-length, concept-evolution, feature-evolution and concept-drift. Infinite-length is due to the continuous nature of data. Concept-evolution is due to the new emerging classes. Concept-drift is due to the drifting concept of the stream and feature-evolution is there because of the changing features. These challenges have been well studied by various researchers and they have proposed various approaches to handle them. In this paper we also try to propose a strategy based on strings to handle the problems of infinite-length, concept-evolution and concept-drift.
Keywords: mining, novel, concept-drift, concept-evolution