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open access

Unsupervised Large-Vocabulary Word Sense Disambiguation with Graph-based Algorithms for Sequence Data Labeling

Description: This paper introduces a graph-based algorithm for sequence data labeling, using random walks on graphs encoding label dependencies. The algorithm is illustrated and tested in the context of an unsupervised word sense disambiguation problem, and shown to significantly outperform the accuracy achieved through individual label assignment, as measured on standard sense-annotated data sets.
Date: October 2005
Creator: Mihalcea, Rada, 1974-
Partner: UNT College of Engineering
open access

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
open access

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
open access

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
open access

Wikify! Linking Documents to Encyclopedic Knowledge

Description: This paper introduces the use of Wikipedia as a resource for automatic keyword extraction and word sense disambiguation, and shows how this online encyclopedia can be used to achieve state-of-the-art results on both these tasks.
Date: November 2007
Creator: Mihalcea, Rada, 1974- & Csomai, Andras
Partner: UNT College of Engineering
open access

Networks and Natural Language Processing

Description: Article discussing networks and natural language processing. The authors present some of the most successful graph-based representations and algorithms used in language processing and try to explain how and why they work.
Date: September 2008
Creator: Radev, Dragomir R. & Mihalcea, Rada, 1974-
Partner: UNT College of Engineering
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