Information retrieval using a singular value decomposition model of latent semantic structure
SIGIR '88 Proceedings of the 11th annual international ACM SIGIR conference on Research and development in information retrieval
Machine Learning - Special issue on applications in molecular biology
Learning human-like knowledge by singular value decomposition: a progress report
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
CHI '82 Proceedings of the 1982 Conference on Human Factors in Computing Systems
Summary street: an intelligent tutoring system for improving student writing through the use of latent semantic analysis
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This paper reports on our experiences using a Creative Requirements [1] workshop approach to elicit requirements for a Grid-based automatic marking system. The research was conducted for ELeGI, an EU funded project whose goal is to provide a European Learning Grid infrastructure to promote a learning paradigm shift from a teacher-centred approach to a learner-centred approach. The automatic marking system uses Latent Semantic Analysis (LSA) to assess the meaning of essays written by computer science students. We foresee the marking system to be a service offered by the Learning Grid. The Creative Requirements Workshop used eight creativity triggers and testimony from an expert witness to elicit creative requirements from the participants. The participants in the workshop produced over 200 requirements in about two hours.