ABSTRACT Data Stream Mining is the process of extracting knowledge structures from
continuous, rapid data records. In these applications, the main goal is to predict the class or …

Now a day's increase in access of video-based application has opened need for extracting
the content in videos. Unprocessed data and low-level features alone are not sufficient to …

Data stream mining is a process of extracting knowledge from continuous data. Data Stream
classification is major challenges than classifying static data because of several unique …

Recent research shows that rule based models perform well while classifying large data sets
such as data streams with concept drifts. A genetic algorithm is a strong rule based …

Data StreamMining 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 …

Recently advancement in hardware and software has enabled processing of large amount
of data efficiently. Many applications generate big data rapidly in high fluctuating rates. The …

Data streams mining has become interesting research topic and growing interest in
knowledge discovery process. Because of the high speed and huge size of data and mining …

Stream data are sequence of data examples that continuously arrive at time-varying and
possibly unbound streams. These data streams are potentially huge in size and thus it is …

Mining data streams is concerned with extracting knowledge structures represented in
models and patterns in high-speed streams of information. It raises new problems for the …