Description: Abstract: This paper describes experiments in metadata generation for learning object repositories. Specifically, the authors present several methods for automatic keyword extraction and evaluate them on a collection of learning objects from an undergraduate history course. The results suggest that automatic keyword extraction is a viable solution for suggesting terms and phrases for metadata annotation.

Description: 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.