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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

Quantifying the Limits and Success of Extractive Summarization Systems Across Domains

Description: This paper analyzes the topic identification stage of single-document automatic text summarization across four different domains, consisting of newswire, literary, scientific and legal documents.
Date: June 2010
Creator: Ceylan, Hakan; Mihalcea, Rada, 1974-; Ozertem, Umut; Lloret, Elena & Palomar, Manuel
Partner: UNT College of Engineering

Text Mining for Automatic Image Tagging

Description: This paper introduces several extractive approaches for automatic image tagging, relying exclusively on information mined from texts. Through evaluations on two datasets, the authors show that their methods exceed competitive baselines by a large margin, and compare favorably with the state-of-the-art that uses both textual and image features.
Date: August 2010
Creator: Leong, Chee Wee; Mihalcea, Rada, 1974- & Hassan, Samer
Partner: UNT College of Engineering

Word Sense and Subjectivity

Description: This paper discusses word sense and subjectivity.
Date: July 2006
Creator: Wiebe, Janyce M. & Mihalcea, Rada, 1974-
Partner: UNT College of Engineering

Characterizing Humour: An Exploration of Features in Humorous Texts

Description: This paper investigates the problem of automatic humor recognition, and provides an in-depth analysis of two of the most frequently observed features of humorous text: human-centeredness and negative polarity. Through experiments performed on two collections of humorous texts, the authors show that these properties of verbal humor are consisted across different data sets.
Date: February 2007
Creator: Mihalcea, Rada, 1974- & Pulman, Stephen
Partner: UNT College of Engineering

Using Wikipedia for Automatic Word Sense Disambiguation

Description: This paper describes a method for generating sense-tagged data using Wikipedia as a source of sense annotations. Through word sense disambiguation experiments, the authors show that the Wikipedia-based sense annotations are reliable and can be used to construct accurate sense classifiers.
Date: April 2007
Creator: Mihalcea, Rada, 1974-
Partner: UNT College of Engineering

Retention and Recruitment of Women in Computer Engineering

Description: This paper describes the efforts and results of a plan for actively recruiting women students to undergraduate computer engineering programs at the University of North Texas (UNT). It also describes a series of activities aimed at improving retention rates of women students already in our programs. Such recruitment and retention of women is critical to the country's efforts to increase the number of engineering professionals, and is a priority for the Computer Science and Engineering (CSE) Department at UNT.
Date: July 2006
Creator: Akl, Robert G. & Garlick, Ryan
Partner: UNT College of Engineering

Simulation of Throughput in UMTS Networks with Different Spreading Factors

Description: In this paper, the authors design and implement a local session admission control (SAC) algorithm for third-generation wireless networks which allows for the simulation of network throughput for different spreading factors and various mobility scenarios.
Date: September 2006
Creator: Akl, Robert G. & Arepally, Anurag
Partner: UNT College of Engineering