This paper considers the use of computational stylistics for performing authorship attribution of electronic messages, addressing categorization problems with as many as 20 differ...
Shlomo Argamon, Marin Saric, Sterling Stuart Stein
In this work we show that verbs reliably represent texts when machine learning algorithms are used to learn opinions. We identify semantic verb categories that capture essential pr...
Detecting conflicting statements is a foundational text understanding task with applications in information analysis. We propose an appropriate definition of contradiction for NLP...
Marie-Catherine de Marneffe, Anna N. Rafferty, Chr...
We investigate the problem of learning document classifiers in a multilingual setting, from collections where labels are only partially available. We address this problem in the ...
Text classification is the process of classifying documents into predefined categories based on their content. Existing supervised learning algorithms to automatically classify te...