Search Results

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

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

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

Co-training and Self-training for Word Sense Disambiguation

Description: This paper investigates the application of co-training and self-training to word sense disambiguation. Optimal and empirical parameter selection methods for co-training and self-training are investigated, with various degrees of error reduction. A new method that combines co-training with majority voting is introduced, with the effect of smoothing the bootstrapping learning curves, and improving the average performance.
Date: May 2004
Creator: Mihalcea, Rada, 1974-
Partner: UNT College of Engineering

The Semantic Wildcard

Description: This paper introduces the semantic wildcard, one of the most powerful operators implemented in IRSLO, which allows for searches along general-specific lines.
Date: May 2002
Creator: Mihalcea, Rada, 1974-
Partner: UNT College of Engineering

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