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» Visually Controllable Data Mining Methods
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AIED
2009
Springer
14 years 1 months ago
Detecting the Learning Value of Items In a Randomized Problem Set
Researchers that make tutoring systems would like to know which pieces of educational content are most effective at promoting learning among their students. Randomized controlled e...
Zachary A. Pardos, Neil T. Heffernan
HASE
1998
IEEE
13 years 11 months ago
Estimating the Number of Residual Defects
Residual defects is one of the most important factors that allow one to decide if a piece of software is ready to be released. In theory, one can find all the defects and count th...
Yashwant K. Malaiya, Jason Denton
ICIP
2010
IEEE
13 years 4 months ago
Building Emerging Pattern (EP) Random forest for recognition
The Random forest classifier comes to be the working horse for visual recognition community. It predicts the class label of an input data by aggregating the votes of multiple tree...
Liang Wang, Yizhou Wang, Debin Zhao
RECSYS
2010
ACM
13 years 7 months ago
Incremental collaborative filtering via evolutionary co-clustering
Collaborative filtering is a popular approach for building recommender systems. Current collaborative filtering algorithms are accurate but also computationally expensive, and so ...
Mohammad Khoshneshin, W. Nick Street
VISUALIZATION
1997
IEEE
13 years 11 months ago
Multiresolution compression and reconstruction
This paper presents a framework for multiresolution compression and geometric reconstruction of arbitrarily dimensioned data designed for distributed applications. Although being ...
Oliver G. Staadt, Markus H. Gross, Roger Weber