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INFORMATICALT
2008
196views more  INFORMATICALT 2008»
15 years 4 months ago
An Efficient and Sensitive Decision Tree Approach to Mining Concept-Drifting Data Streams
Abstract. Data stream mining has become a novel research topic of growing interest in knowledge discovery. Most proposed algorithms for data stream mining assume that each data blo...
Cheng-Jung Tsai, Chien-I Lee, Wei-Pang Yang
ICMCS
2009
IEEE
131views Multimedia» more  ICMCS 2009»
15 years 1 months ago
Web image mining using concept sensitive Markov stationary features
With the explosive growth of web resources, how to mine semantically relevant images efficiently becomes a challenging and necessary task. In this paper, we propose a concept sens...
Chunjie Zhang, Jing Liu, Hanqing Lu, Songde Ma
ICDM
2008
IEEE
145views Data Mining» more  ICDM 2008»
15 years 10 months ago
Paired Learners for Concept Drift
To cope with concept drift, we paired a stable online learner with a reactive one. A stable learner predicts based on all of its experience, whereas a reactive learner predicts ba...
Stephen H. Bach, Marcus A. Maloof
CLEF
2008
Springer
15 years 5 months ago
Using Visual Concepts and Fast Visual Diversity to Improve Image Retrieval
In this article, we focus our efforts (i) on the study of how to automatically extract and exploit visual concepts and (ii) on fast visual diversity. First, in the Visual Concept D...
Sabrina Tollari, Marcin Detyniecki, Ali Fakeri-Tab...
AOSD
2009
ACM
15 years 1 months ago
Concept analysis for product line requirements
Traditional methods characterize a software product line's requirements using either functional or quality criteria. This appears to be inadequate to assess modularity, detec...
Nan Niu, Steve M. Easterbrook