UNT Scholarly Works - 403 Matching Results

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The Decomposition of Human-Written Book Summaries

Description: In this paper, the authors evaluate the extent to which human-written book summaries can be obtained through cut-and-paste operations from the original book. The authors analyze the effect of the parameters involved in the decomposition algorithm, and highlight the distinctions in coverage obtained for different summary types.
Date: March 2009
Creator: Ceylan, Hakan & Mihalcea, Rada, 1974-
Partner: UNT College of Engineering

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

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

Graph-based Ranking Algorithms for Sentence Extraction, Applied to Text Summarization

Description: Abstract: This paper presents an innovative unsupervised method for automatic sentence extraction using graph-based ranking algorithms. We evaluate the method in the context of a text summarization task, and show that the results obtained compare favorably with previously published results on established benchmarks.
Date: July 2004
Creator: Mihalcea, Rada, 1974-
Partner: UNT College of Engineering

SenseLearner: Minimally Supervised Word Sense Disambiguation for All Words in Open Text

Description: This paper introduces SenseLearner - a minimally supervised sense tagger that attempts to disambiguate all content words in a text using the sense from WordNet. SenseLearner participated in the SENSEVAL-3 English all words task, and achieved an average accuracy of 64.6%.
Date: 2004
Creator: Mihalcea, Rada, 1974- & Faruque, Ehsanul
Partner: UNT College of Engineering

TextRank: Bringing Order into Texts

Description: In this paper, the authors introduce TextRank, a graph-based ranking model for text processing, and show how this model can be successfully used in natural language applications.
Date: July 2004
Creator: Mihalcea, Rada, 1974- & Tarau, Paul
Partner: UNT College of Engineering

The SENSEVAL-3 English Lexical Sample Task

Description: This paper presents the task definition, resources, participating systems, and comparative results for the English lexical sample task, which was organized as part of the SENSEVAL-3 evaluation exercise.
Date: July 2004
Creator: Mihalcea, Rada, 1974-; Chklovski, Timothy A. (Timothy Anatolievich), 1977- & Kilgarriff, Adam
Partner: UNT College of Engineering

Word Alignment for Languages with Scarce Resources

Description: This paper presents the task definition, resources, participating systems, and comparative results for the shared task on word alignment which was organized as part of the Association for Computational Linguistics (ACL) 2005 Workshop on Building and Using Parallel Texts. The shared task included English-Inuktitut, Romanian-English, and English-Hindi sub-tasks, and drew the participation of ten teams from around the world with a total of 50 systems.
Date: June 2005
Creator: Martin, Joel; Mihalcea, Rada, 1974- & Pedersen, Ted
Partner: UNT College of Engineering