75 search results - page 2 / 15 » Building Text Classifiers Using Positive and Unlabeled Examp... |
ECML
2005
Springer
13 years 10 months ago
2005
Springer
Abstract. We study the problem of learning from positive and unlabeled examples. Although several techniques exist for dealing with this problem, they all assume that positive exam...
IJCAI
2007
13 years 6 months ago
2007
Traditional classification involves building a classifier using labeled training examples from a set of predefined classes and then applying the classifier to classify test instan...
WAIM
2010
Springer
13 years 10 months ago
2010
Springer
Abstract. The problem of classification from positive and unlabeled examples attracts much attention currently. However, when the number of unlabeled negative examples is very sma...
EMNLP
2008
13 years 6 months ago
2008
We present a discriminative method for learning selectional preferences from unlabeled text. Positive examples are taken from observed predicate-argument pairs, while negatives ar...
MLDM
2007
Springer
13 years 11 months ago
2007
Springer
This paper presents a novel solution for the problem of building text classifier using positive documents (P) and unlabeled documents (U). Here, the unlabeled documents are mixed w...