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» Methods for finding frequent items in data streams
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CIKM
2001
Springer
14 years 6 days ago
Ordinal Association Rules for Error Identification in Data Sets
A new extension of the Boolean association rules, ordinal association rules, that incorporates ordinal relationships among data items, is introduced. One use for ordinal rules is ...
Andrian Marcus, Jonathan I. Maletic, King-Ip Lin
KDD
2006
ACM
200views Data Mining» more  KDD 2006»
14 years 8 months ago
A Random-Walk Based Scoring Algorithm Applied to Recommender Engines
Recommender systems are an emerging technology that helps consumers find interesting products and useful resources. A recommender system makes personalized product suggestions by e...
Augusto Pucci, Marco Gori, Marco Maggini
DAWAK
1999
Springer
13 years 12 months ago
Mining Interval Time Series
Data mining can be used to extensively automate the data analysis process. Techniques for mining interval time series, however, have not been considered. Such time series are commo...
Roy Villafane, Kien A. Hua, Duc A. Tran, Basab Mau...
DSMML
2004
Springer
14 years 1 months ago
Redundant Bit Vectors for Quickly Searching High-Dimensional Regions
Applications such as audio fingerprinting require search in high dimensions: find an item in a database that is similar to a query. An important property of this search task is t...
Jonathan Goldstein, John C. Platt, Christopher J. ...
JCIT
2010
174views more  JCIT 2010»
13 years 2 months ago
Efficient Ming of Top-K Closed Sequences
Sequence mining is an important data mining task. In order to retrieve interesting sequences from a large database, a minimum support threshold is needed to be specified. Unfortun...
Panida Songram