ISCAS OpenIR  > 人机交互技术与智能信息处理实验室
mining recent frequent itemsets in data streams
Li Kun; Wang Yong-yan; Ellahi Manzoor; Wang Hong-an
2008
Conference Name5th International Conference on Fuzzy Systems and Knowledge Discovery
SourceProceedings - 5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008
Pages353-358
Conference DateOCT 18-20,
Conference PlaceJinan, PEOPLES R CHINA
Publish Place10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA
PublisherFIFTH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, VOL 4, PROCEEDINGS
ISBN978-0-7695-3305-6
DepartmentLi, Kun; Wang, Yong-yan; Ellahi, Manzoor; Wang, Hong-an Chinese Acad Sci, Inst Software, Intelligence Engn Lab, Beijing 100190, Peoples R China.
English AbstractMining frequent itemsets in data streams is a hot research topic in recent years. Due to the continuous, highspeed and unbounded properties of data streams, traditional algorithms on static dataset are not suitable for mining in data streams.
KeywordBfi-stream Mfi-transsw Bounded Frequent Itemsets Stream Data Streams Prefix-tree Based Structure Data Mining Tree Data Structures
SponsorshipShandong Univ, Int Nat Computat & Knowledge Discovery Assoc
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/10642
Collection人机交互技术与智能信息处理实验室
Recommended Citation
GB/T 7714
Li Kun,Wang Yong-yan,Ellahi Manzoor,et al. mining recent frequent itemsets in data streams[C]. 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA:FIFTH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, VOL 4, PROCEEDINGS,2008:353-358.
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