An architecture for context-aware adaptive data stream mining

author: Mohamed Medhat Gaber, Monash University
published: Jan. 29, 2008,   recorded: September 2007,   views: 5522

Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.


In resource-constrained devices, adaptation of data stream processing to variations of data rates, availability of resources and environment changes is crucial for consistency and continuity of running applications. Context-aware adaptation, as a new dimension of research in data stream mining, enhances and optimizes distributed data stream processing tasks. Context-awareness is one of the key aspects of ubiquitous computing as applicationsC¸ successful operations rely on detecting changes and adjusting accordingly. This paper presents a general architecture for context-aware adaptive mining of data streams that aims to dynamically and autonomously adjust data stream mining parameters according to changes in context and resource availability in distributed and heterogeneous computing environments.

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: