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ECAI
2008
Springer
13 years 9 months ago
An Ensemble of Classifiers for coping with Recurring Contexts in Data Streams
Abstract. This paper proposes a general framework for classifying data streams by exploiting incremental clustering in order to dynamically build and update an ensemble of incremen...
Ioannis Katakis, Grigorios Tsoumakas, Ioannis P. V...
ICDE
2008
IEEE
153views Database» more  ICDE 2008»
14 years 9 months ago
A Framework for Clustering Uncertain Data Streams
Abstract-- In recent years, uncertain data management applications have grown in importance because of the large number of hardware applications which measure data approximately. F...
Charu C. Aggarwal, Philip S. Yu
SAC
2009
ACM
14 years 2 months ago
Parameterless outlier detection in data streams
Outlyingness is a subjective concept relying on the isolation level of a (set of) record(s). Clustering-based outlier detection is a field that aims to cluster data and to detect...
Alice Marascu, Florent Masseglia
APPROX
2008
Springer
101views Algorithms» more  APPROX 2008»
13 years 9 months ago
Streaming Algorithms for k-Center Clustering with Outliers and with Anonymity
Clustering is a common problem in the analysis of large data sets. Streaming algorithms, which make a single pass over the data set using small working memory and produce a cluster...
Richard Matthew McCutchen, Samir Khuller
CORR
2010
Springer
138views Education» more  CORR 2010»
13 years 7 months ago
Data Stream Clustering: Challenges and Issues
Very large databases are required to store massive amounts of data that are continuously inserted and queried. Analyzing huge data sets and extracting valuable pattern in many appl...
Madjid Khalilian, Norwati Mustapha