UM
Framework of Temporal Data Stream Mining by Using Incrementally Optimized Very Fast Decision Forest
Fong, Simon; Song, Wei; Wong, Raymond; Bhatt, Chintan; Korzun, Dmitry; Dey, N; Hassanien, AE; Bhatt, C; Ashour, AS; Satapathy, SC
2018
Source PublicationINTERNET OF THINGS AND BIG DATA ANALYTICS TOWARD NEXT-GENERATION INTELLIGENCE
ISSN2197-6503
Volume30Pages:483-502
AbstractIncrementally Optimized Very Fast Decision Tree (iOVFDT) is a new data stream mining model that optimizes a balance of compact tree size and prediction accuracy. The iOVFDT was developed into open source on Massive Online Analysis as a prior art. In this book chapter, we review related techniques and extend iOVFDT into iOVFDF ('F' for forest of Trees) for temporal data stream mining. A framework for follow-up research is reported in this article. A major issue to the current temporal data mining algorithms is due to the inherent limitation of batch learning. But in real-life, the hidden concepts of data streams may change rapidly, and the data may amount to infinity. In the big Data era, incremental learning is attractive since it does not require processing the full volume of dataset. Under this framework we propose to research and develop a new breed of temporal data stream algorithms-iOVFDF. We integrate for a "meta-classifier" called iOVFD Forest over a collection of iOVFDT classifiers. The new iOVFD Forest can incrementally learn temporal associations across multiple time-series in real-time, while each underlying individual iOVFDTree learns and recognizes sub-sequence patterns dynamically.
KeywordData stream mining Decision trees Meta-classifiers Big data
DOI10.1007/978-3-319-60435-0_19
URLView the original
Indexed ByBSCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Information Systems ; Computer Science, Theory & Methods
WOS IDWOS:000429534000020
PublisherSPRINGER-VERLAG BERLIN
The Source to ArticleWOS
Fulltext Access
Citation statistics
Cited Times [WOS]:2   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Recommended Citation
GB/T 7714
Fong, Simon,Song, Wei,Wong, Raymond,et al. Framework of Temporal Data Stream Mining by Using Incrementally Optimized Very Fast Decision Forest[J]. INTERNET OF THINGS AND BIG DATA ANALYTICS TOWARD NEXT-GENERATION INTELLIGENCE,2018,30:483-502.
APA Fong, Simon.,Song, Wei.,Wong, Raymond.,Bhatt, Chintan.,Korzun, Dmitry.,...&Satapathy, SC.(2018).Framework of Temporal Data Stream Mining by Using Incrementally Optimized Very Fast Decision Forest.INTERNET OF THINGS AND BIG DATA ANALYTICS TOWARD NEXT-GENERATION INTELLIGENCE,30,483-502.
MLA Fong, Simon,et al."Framework of Temporal Data Stream Mining by Using Incrementally Optimized Very Fast Decision Forest".INTERNET OF THINGS AND BIG DATA ANALYTICS TOWARD NEXT-GENERATION INTELLIGENCE 30(2018):483-502.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Fong, Simon]'s Articles
[Song, Wei]'s Articles
[Wong, Raymond]'s Articles
Baidu academic
Similar articles in Baidu academic
[Fong, Simon]'s Articles
[Song, Wei]'s Articles
[Wong, Raymond]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Fong, Simon]'s Articles
[Song, Wei]'s Articles
[Wong, Raymond]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.