Extractive summaries for educational science content

Authors:
Sebastian de la Chica;Faisal Ahmad;James H. Martin;Tamara Sumner
Affiliations:
University of Colorado at Boulder;University of Colorado at Boulder;University of Colorado at Boulder;University of Colorado at Boulder
Venue:
HLT-Short '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers
Year:
2008

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Abstract

This paper describes an extractive summarizer for educational science content called COGENT. COGENT extends MEAD based on strategies elicited from an empirical study with domain and instructional experts. COGENT implements a hybrid approach integrating both domain independent sentence scoring features and domain-aware features. Initial evaluation results indicate that COGENT outperforms existing summarizers and generates summaries that closely resemble those generated by human experts.