315 search results - page 2 / 63 » Text classification from positive and unlabeled documents |
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...
NIPS
2008
13 years 6 months ago
2008
In this paper, we address the question of what kind of knowledge is generally transferable from unlabeled text. We suggest and analyze the semantic correlation of words as a gener...
ICML
2007
IEEE
14 years 6 months ago
2007
IEEE
We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...
ICML
2003
IEEE
14 years 6 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...
NIPS
2008
13 years 6 months ago
2008
The cluster assumption is exploited by most semi-supervised learning (SSL) methods. However, if the unlabeled data is merely weakly related to the target classes, it becomes quest...