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» Learning missing values from summary constraints
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COLING
2010
13 years 1 months ago
Grouping Product Features Using Semi-Supervised Learning with Soft-Constraints
In opinion mining of product reviews, one often wants to produce a summary of opinions based on product features/attributes. However, for the same feature, people can express it w...
Zhongwu Zhai, Bing Liu, Hua Xu, Peifa Jia
UML
2005
Springer
13 years 11 months ago
Lessons Learned from Developing a Dynamic OCL Constraint Enforcement Tool for Java
Analysis and design by contract allows the definition of a formal agreement between a class and its clients, expressing each party’s rights and obligations. Contracts written in ...
Wojciech J. Dzidek, Lionel C. Briand, Yvan Labiche
JMLR
2008
104views more  JMLR 2008»
13 years 6 months ago
Learning Reliable Classifiers From Small or Incomplete Data Sets: The Naive Credal Classifier 2
In this paper, the naive credal classifier, which is a set-valued counterpart of naive Bayes, is extended to a general and flexible treatment of incomplete data, yielding a new cl...
Giorgio Corani, Marco Zaffalon
PVLDB
2010
82views more  PVLDB 2010»
13 years 4 months ago
Record Linkage with Uniqueness Constraints and Erroneous Values
Many data-management applications require integrating data from a variety of sources, where different sources may refer to the same real-world entity in different ways and some ma...
Songtao Guo, Xin Dong, Divesh Srivastava, Remi Zaj...
CVPR
2005
IEEE
14 years 8 months ago
Robust L1 Norm Factorization in the Presence of Outliers and Missing Data by Alternative Convex Programming
Matrix factorization has many applications in computer vision. Singular Value Decomposition (SVD) is the standard algorithm for factorization. When there are outliers and missing ...
Qifa Ke, Takeo Kanade