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Topic Identification Using Wikipedia Graph Centrality

Description: This paper presents a method for automatic topic identification using a graph-centrality algorithm applied to an encyclopedic graph derived from Wikipedia. When tested on a data set with manually assigned topics, the system is found to significantly improve over a simpler baseline that does not make use of the external encyclopedic knowledge.
Date: May 2009
Creator: Coursey, Kino High & Mihalcea, Rada, 1974-
Partner: UNT College of Engineering
open access

Using Encyclopedic Knowledge for Automatic Topic Identification

Description: This paper presents a method for automatic topic identification using an encyclopedic graph derived from Wikipedia. The system is found to exceed the performance of previously proposed machine learning algorithms for topic identification, with an annotation consistency comparable to human annotations.
Date: May 2009
Creator: Coursey, Kino High; Mihalcea, Rada, 1974- & Moen, William E.
Partner: UNT College of Engineering
open access

Amazon Mechanical Turk for Subjectivity Word Sense Disambiguation

Description: In this paper, the authors discuss research on whether they can use Mechanical Turk (MTurk) to acquire good annotations with respect to gold-standard data, whether they can filter out low-quality workers (spammers), and whether there is a learning effect associated with repeatedly completing the same kind of task.
Date: June 2010
Creator: Akkaya, Cem; Conrad, Alexander; Wiebe, Janyce M. & Mihalcea, Rada, 1974-
Partner: UNT College of Engineering
open access

Topic Modeling on Historical Newspapers

Description: Paper for the 2011 ACL Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities. This paper discusses topic modeling on historical newspaper.
Date: June 2011
Creator: Yang, Tze-I; Torget, Andrew J., 1978- & Mihalcea, Rada, 1974-
Partner: UNT College of Arts and Sciences
open access

Subjectivity Word Sense Disambiguation

Description: This paper investigates a new task, subjectivity word sense disambiguation (SWSD), which is to automatically determine which word instances in a corpus are being used with subjective senses, and which are being used with objective senses.
Date: August 2009
Creator: Akkaya, Cem; Wiebe, Janyce M. & Mihalcea, Rada, 1974-
Partner: UNT College of Engineering
open access

SemEval-2007 Task 14: Affective Text

Description: The "Affective Text" task focuses on the classification of emotions and valence (positive/negative polarity) in news headlines, and is meant as an exploration of the connection between emotions and lexical semantics. In this paper, the authors describe the data set used in the evaluation and the results obtained by the participating systems.
Date: June 2007
Creator: Strapparava, Carlo, 1962- & Mihalcea, Rada, 1974-
Partner: UNT College of Engineering
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