Investigating the impact of bursty traffic on Hoeffding Tree Algorithm in stream mining over internet
Yang Hang; Simon Fong
2010-12-13
Conference Name2010 2nd International Conference on Evolving Internet
Source PublicationProceedings - 2nd International Conference on Evolving Internet, Internet 2010, 1st International Conference on Access Networks, Services and Technologies, Access 2010
Pages147-152
Conference Date20-25 Sept. 2010
Conference PlaceValcencia, Spain
Abstract

Stream data are continuous and ubiquitous in nature which can be found in many Web applications operating on Internet. Some instances of stream data are web logs, online users' click-streams, online media streaming and Web transaction records. Stream Mining was proposed as a relatively new data analytic solution for handling such streams. It has been widely acclaimed of its usefulness in real-time decision-support applications, for example web recommenders. Hoeffding Tree Algorithm (HTA) is one of the popular choices for implementing Very Fast Decision Tree (VFDT) in stream mining. The theoretical aspects have been studied extensively by researchers. However, the data streams that fed into HTA are usually assumed at a constant rate in the literature. HTA has yet been tested under bursty traffic such as Internet environment. This paper sheds some light into the impact of bursty traffic on the performance of HTA in stream mining. © 2010 IEEE.

KeywordBursty Stream Hoeffding Tree Algorithm Real-time Application Stream Mining
DOIhttp://doi.org/10.1109/INTERNET.2010.33
URLView the original
Language英语
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Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
AffiliationFaculty of Science and Technology University of Macau Macau SAR, China
First Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Yang Hang,Simon Fong. Investigating the impact of bursty traffic on Hoeffding Tree Algorithm in stream mining over internet[C],2010:147-152.
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