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» A New Support Vector Machine for Data Mining
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IJCNN
2006
IEEE
14 years 1 months ago
Adaptation of Artificial Neural Networks Avoiding Catastrophic Forgetting
— In connectionist learning, one relevant problem is “catastrophic forgetting” that may occur when a network, trained with a large set of patterns, has to learn new input pat...
Dario Albesano, Roberto Gemello, Pietro Laface, Fr...
GFKL
2005
Springer
142views Data Mining» more  GFKL 2005»
14 years 27 days ago
Near Similarity Search and Plagiarism Analysis
Abstract. Existing methods to text plagiarism analysis mainly base on “chunking”, a process of grouping a text into meaningful units each of which gets encoded by an integer nu...
Benno Stein, Sven Meyer zu Eissen
BMCBI
2008
175views more  BMCBI 2008»
13 years 7 months ago
Synonym set extraction from the biomedical literature by lexical pattern discovery
Background: Although there are a large number of thesauri for the biomedical domain many of them lack coverage in terms and their variant forms. Automatic thesaurus construction b...
John McCrae, Nigel Collier
CIKM
2010
Springer
13 years 4 months ago
Regularization and feature selection for networked features
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
Hongliang Fei, Brian Quanz, Jun Huan
EXACT
2009
13 years 5 months ago
Explaining a Result to the End-User: A Geometric Approach for Classification Problems
This paper addresses the issue of the explanation of the result given to the end-user by a classifier, when it is used as a decision support system. We consider machine learning cl...
Isabelle Alvarez, Sophie Martin