286 search results - page 4 / 58 » Learning to Classify Texts Using Positive and Unlabeled Data |
CASCON
2001
13 years 7 months ago
2001
The main problems in text classification are lack of labeled data, as well as the cost of labeling the unlabeled data. We address these problems by exploring co-training - an algo...
ICML
2003
IEEE
14 years 7 months ago
2003
IEEE
The problem of learning with positive and unlabeled examples arises frequently in retrieval applications. We transform the problem into a problem of learning with noise by labelin...
CVPR
2003
IEEE
14 years 8 months ago
2003
IEEE
Understanding human emotions is one of the necessary skills for the computer to interact intelligently with human users. The most expressive way humans display emotions is through...
MLDM
2007
Springer
14 years 16 days 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...
CICLING
2004
Springer
13 years 11 months ago
2004
Springer
When text categorization is applied to complex tasks, it is tedious and expensive to hand-label the large amounts of training data necessary for good performance. In this paper, we...