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...
In automated text categorization, given a small number of labeled documents, it is very challenging, if not impossible, to build a reliable classifier that is able to achieve high...
Zenglin Xu, Rong Jin, Kaizhu Huang, Michael R. Lyu...
Supervised text classification is the task of automatically assigning a category label to a previously unlabeled text document. We start with a collection of pre-labeled examples ...
Temporal reasoners for document understanding typically assume that a document’s creation date is known. Algorithms to ground relative time expressions and order events often re...
A significant portion of the world's text is tagged by readers on social bookmarking websites. Credit attribution is an inherent problem in these corpora because most pages h...
Daniel Ramage, David Hall, Ramesh Nallapati, Chris...