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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

The SENSEVAL-3 Multilingual English-Hindi Lexical Sample Task

Description: This paper describes the English-Hindi Multilingual lexical sample task in SENSEVAL-3.
Date: July 2004
Creator: Chklovski, Timothy A. (Timothy Anatolievich), 1977-; Mihalcea, Rada, 1974-; Pedersen, Ted & Purandare, Amruta
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

PicNet: Augmenting Semantic Resources with Pictorial Representations

Description: In this paper, the authors introduce PicNet, a Web-based system for augmenting semantic resources with illustrative images using volunteer contributions over the Web.
Date: March 2005
Creator: Borman, Andy; Mihalcea, Rada, 1974- & Tarau, Paul
Partner: UNT College of Engineering

Text Semantic Similarity, with Applications

Description: In this paper, the authors present a knowledge-based method for measuring the semantic-similarity of texts. Through experiments performed on two different applications: (1) paraphrase and entailment identification, and (2) word sense similarity, the authors show that this method outperforms the traditional text similarity metrics based on lexical matching.
Date: September 2005
Creator: Corley, Courtney; Csomai, Andras & Mihalcea, Rada, 1974-
Partner: UNT College of Engineering

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