DATA STREAM MINING ALGORITHMS – A REVIEW OF ISSUES AND EXISTING APPROACHES
Journal Title: International Journal on Computer Science and Engineering - Year 2011, Vol 3, Issue 7
Abstract
More and more applications such as traffic modeling, military sensing and tracking, online data processing etc., generate a large amount of data streams every day. Efficient knowledge discovery of such data streams is an emerging active research area in data mining with broad applications. Different from data in traditional static databases, data streams typically arrive continuously in high speed with huge amount and changing data distribution. This raises new issues that need to be considered when developing association rule mining techniques for stream data. Due to the unique features of data stream, traditional data mining techniques which require multiple scans of the entire data sets can not be applied directly to mine stream data, which usually allows only one scan and demands fast response time.
Authors and Affiliations
A. Mala , F. Ramesh Dhanaseelan
Keywords
Related Articles
- EP ID EP108191
- DOI -
- Views 95
- Downloads 0
Secure Transmission of Compound Information Using Image Steganography
The security of information handled in real time transmission reception like internet is of paramount consideration, as this information may be confidential. And also, the parameter in concern nowa- days is size as it ma...
A novel method of dynamic permanent caching with resourceful built up and imperative access
Caching is built up each time when the machine starts up according to user’s application usability. This built up rocedure escalates the efficiency of application’s usage for the next coming access of same application....
MRI Brain Image Tissue Segmentation analysis using Possibilistic Fuzzy C-means Method
In this paper, we analyzed the segmentation of MRI brain image into different tissue types on brain image using Possibilistic fuzzy c-means (PFCM) clustering. Application of this method to MRI brain image gives the bette...
Performance Evaluation of Mutation / Non- Mutation Based Classification With Missing Data
A common problem encountered by many data mining techniques is the missing data. A missing data is defined as an attribute or feature in a dataset which has no associated data value. Correct treatment of these data is cr...
Application of fuzzy-AHP extent analysis to determine the relative importance of risk factors in operative mortality after Coronary Artery Bypass surgery
The goal of this study is to recognize most important risk factors associated with surgical mortality in patient who underwent CABG by the integration of fuzzy concept and analytical hierarchy process method to represent...