Cross-language Text Categorization is the task of assigning semantic classes to documents written in a target language (e.g. English) while the system is trained using labeled doc...
When humans approach the task of text categorization, they interpret the specific wording of the document in the much larger context of their background knowledge and experience. ...
PROBLEM: Automatic keyword assignment has been largely studied in medical informatics in the context of the MEDLINE database, both for helping search in MEDLINE and in order to pr...
We describe the creation of a corpus that supports a real-world hierarchical text categorization task in the domain of electronic rulemaking (eRulemaking). Features of the task an...
Claire Cardie, Cynthia Farina, Matt Rawding, Adil ...
We address the e-rulemaking problem of categorizing public comments according to the issues that they address. In contrast to previous text categorization research in e-rulemaking...
Claire Cardie, Cynthia Farina, Adil Aijaz, Matt Ra...
This paper describes a parameter estimation method for multi-label classification that does not rely on approximate inference. It is known that multi-label classification involvin...
Content analysis is often employed by teachers and research to analyse online discussion forums to serve various purposes such as assessment, evaluation, and educational research....
Andrew Kwok-Fai Lui, Siu Cheung Li, Sheung-On Choy
Abstract-- Text categorization is the task of assigning predefined categories to natural language text. With the widely used `bag of words' representation, previous researches...
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...
Abstract. This paper reports our comparative evaluation of three machine learning methods on Chinese text categorization. Whereas a wide range of methods have been applied to Engli...