Data Stream Mining Addresses Research Issues Addressed by the Data Mining Community

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Data stream mining is a stimulating field of study that has raised challenges and research issues to be addressed by the database and data mining communities. The following is a discussion of both addressed and open research issues [19].

Handling the continuous flow of data streams
This is a data management issue. Traditional database management systems are not capable of dealing with such continuous high data rate. Novel indexing, storage and querying techniques are required to handle this non stopping fluctuated flow of information streams.

Minimizing energy consumption of the mobile device
Large amounts of data streams are generated in resource-constrained environments. Sensor networks represent a typical example. These devices
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If the number of clusters generated for example is changed, it might represent some changes in the dynamics of the arriving stream. Dynamics of data streams using changes in the knowledge structures generated would benefit many temporal-based analysis applications.

Developing algorithms for mining results’ changes
This is related to the previous issue. Traditional data mining algorithms do not produce any results that show the change of the results over time.

Visualization of data mining results on small screens of mobile devices
Visualization of traditional data mining results on a desktop is still a research issue. Visualization in small screens of a PDA for example is a real challenge. Imagine a businessman and data are being streamed and analyzed on his PDA. Such results should be efficiently visualized in a way that enables him to take a quick decision.

Interactive mining environment to satisfy user requirements
Mining data streams is a highly application oriented field. The user requirements are considered a vital research problem to be addressed.

The integration between data stream management systems [4, 40] and the ubiquitous data stream mining approaches
It is an essential issue that should be addressed to realize a fully functioning ubiquitous mining. The integration among storage, querying, mining and reasoning over streaming information would realize robust streaming systems that could be used

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