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ICTAI
2007
IEEE
14 years 4 months ago
An Adaptive Distributed Ensemble Approach to Mine Concept-Drifting Data Streams
An adaptive boosting ensemble algorithm for classifying homogeneous distributed data streams is presented. The method builds an ensemble of classifiers by using Genetic Programmi...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
CORR
2010
Springer
138views Education» more  CORR 2010»
13 years 10 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
IEAAIE
2009
Springer
14 years 4 months ago
An Efficient Algorithm for Maintaining Frequent Closed Itemsets over Data Stream
Data mining refers to the process of revealing unknown and potentially useful information from a large database. Frequent itemsets mining is one of the foundational problems in dat...
Show-Jane Yen, Yue-Shi Lee, Cheng-Wei Wu, Chin-Lin...
ICMCS
2006
IEEE
137views Multimedia» more  ICMCS 2006»
14 years 3 months ago
Online Mining of Recent Music Query Streams
Mining multimedia data is one of the most important issues in data mining. In this paper, we propose an online one-pass algorithm to mine the set of frequent temporal patterns in ...
Hua-Fu Li, Chin-Chuan Ho, Man-Kwan Shan, Suh-Yin L...
WSDM
2012
ACM
301views Data Mining» more  WSDM 2012»
12 years 5 months ago
Learning evolving and emerging topics in social media: a dynamic nmf approach with temporal regularization
As massive repositories of real-time human commentary, social media platforms have arguably evolved far beyond passive facilitation of online social interactions. Rapid analysis o...
Ankan Saha, Vikas Sindhwani