Classification and evaluation of data mining techniques for data stream requirements

In recent years, the management and processing of data streams has become a topic of active research in several fields of computer science, such as distributed systems, database systems, and data mining. In data streams´ applications, such as network monitoring, telecommunication systems and sensor networks, because of online monitoring, answering to the user´s queries should be time and space efficient. Generally, two main challenges are to design fast mining methods for data streams and the need to promptly detect changing concepts and data distribution because of highly dynamic nature of data streams. The goal of this article is to analyze and classify the application of diverse data mining techniques in different challenges of data stream mining. For this goal, this article tries to categorize and analyze related researches for better understanding and to reach a framework that can map data mining techniques to data stream mining challenges and requirements.