You limited your search to:
- Automatic Keyword Extraction for Learning Object Repositories
- 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.
- Semantic Document Engineering with WordNet and PageRank
- 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.
- Using Encyclopedic Knowledge for Automatic Topic Identification
- Abstract: 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.