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This article discusses semantic document engineering with WordNet and PageRank.
Physical Description
5 p.
Notes
Abstract: This paper describes natural language processing techniques for document engineering in combination with graph algorithms and statistical methods. Google's PageRank and similar fast-converging recursive graph algorithms have provided practical means to statistically rank vertices of large graphs like the World Wide Web. By combining a fast Java-based PageRank implementation with a Prolog base inferential layer, running on top of an optimized WordNet graph, the authors describe applications to word sense disambiguation and evaluate their accuracy on standard benchmarks.
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Tarau, Paul; Mihalcea, Rada, 1974- & Figa, Elizabeth.Semantic Document Engineering with WordNet and PageRank,
paper,
March 2005;
(https://digital.library.unt.edu/ark:/67531/metadc30974/:
accessed September 9, 2024),
University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu;
crediting UNT College of Engineering.
