Date: September 2004
Creator: Tarau, Paul; Mihalcea, Rada, 1974- & Figa, Elizabeth
Description: This paper discusses a logic programming framework for semantic interpretation with WordNet and PageRank. Abstract: This paper describes applications of Logic Programming to Natural Language processing 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 in comparison with human annotated corpus data.
Contributing Partner: UNT College of Engineering