UNT College of Engineering - 212 Matching Results

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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

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-

Throughput Optimization in Multi-Cell CDMA Networks

Description: In this paper, the authors investigate the performance of a multi-cell CDMA network by determining the maximum throughput that the network can archive for a given grade-of-service requirement, quality-of-service requirement, network topology and call arrival rate profile.
Date: March 2005
Creator: Akl, Robert G.; Naraghi-Pour, Mort & Hegde, Manju V.

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-

Unsupervised Graph-based Word Sense Disambiguation Using Measures of Word Semantic Similarity

Description: This paper describes an unsupervised graph-based method for word sense disambiguation, and presents comparative evaluations using several measures of word semantic similarity and several algorithms for graph centrality. The results indicate that the right combination of similarity metrics and graph centrality algorithms can lead to a performance competing with the state-of-the-art in unsupervised word sense disambiguation, as measured on standard data sets.
Date: September 2007
Creator: Sinha, Ravi & Mihalcea, Rada, 1974-

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-

UNT: SubFinder: Combining Knowledge Sources for Automatic Lexical Substitution

Description: This paper describes the University of North Texas SubFinder system. The system is able to provide the most likely set of substitutes for a word in a given context, by combining several techniques and knowledge sources. SubFinder has successfully participated in the best and out of ten (oot) tracks in the SEMEVAL lexical substitution task, consistently ranking in the first or second place.
Date: June 2007
Creator: Hassan, Samer; Csomai, Andras; Banea, Carmen; Sinha, Ravi & Mihalcea, Rada, 1974-

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.