The University of Michigan in Novelty 2004

This year we participated in the Novelty track. To find the relevant sentences, we combine sentence salience features that are inherited from text summarization domain with other heuristic features based on topic statements. We propose a novel method to extract the new sentences based on the graph-based ranking of the similarity relation between the sentences.

• Type: Conference
• Year: 2004
• Where: TREC
• Authors: Günes Erkan
• Keywords: Relevant Sentences, Sentence Salience Features, Text Summarization Domain, TREC 2004, TREC 2008