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» Mining data streams: a review
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KDD
2004
ACM
117views Data Mining» more  KDD 2004»
14 years 9 months ago
Systematic data selection to mine concept-drifting data streams
One major problem of existing methods to mine data streams is that it makes ad hoc choices to combine most recent data with some amount of old data to search the new hypothesis. T...
Wei Fan
LREC
2010
251views Education» more  LREC 2010»
13 years 10 months ago
Extracting Product Features and Sentiments from Chinese Customer Reviews
With the growing interest in opinion mining from web data, more works are focused on mining in English and Chinese reviews. Probing into the problem of product opinion mining, thi...
Shu Zhang, Wen-Jie Jia, Yingju Xia, Yao Meng, Hao ...
SAC
2006
ACM
14 years 2 months ago
Discretization from data streams: applications to histograms and data mining
Abstract. In this paper we propose a new method to perform incremental discretization. The basic idea is to perform the task in two layers. The first layer receives the sequence o...
João Gama, Carlos Pinto
HICSS
2009
IEEE
190views Biometrics» more  HICSS 2009»
14 years 3 months ago
Real-Time Knowledge Discovery and Dissemination for Intelligence Analysis
This paper describes the issues and challenges for real-time knowledge discovery and then discusses approaches and challenges for real-time data mining and stream mining. Our goal...
Bhavani M. Thuraisingham, Latifur Khan, Murat Kant...
PAKDD
2010
ACM
165views Data Mining» more  PAKDD 2010»
13 years 10 months ago
Classification and Novel Class Detection in Data Streams with Active Mining
We present ActMiner, which addresses four major challenges to data stream classification, namely, infinite length, concept-drift, conceptevolution, and limited labeled data. Most o...
Mohammad M. Masud, Jing Gao, Latifur Khan, Jiawei ...