Paper: Generating Impact-Based Summaries for Scientific Literature

ACL ID P08-1093
Title Generating Impact-Based Summaries for Scientific Literature
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2008
Authors

In this paper, we present a study of a novel summarization problem, i.e., summarizing the impact of a scienti c publication. Given a pa- per and its citation context, we study how to extract sentences that can represent the most in uential content of the paper. We propose language modeling methods for solving this problem, and study how to incorporate fea- tures such as authority and proximity to ac- curately estimate the impact language model. Experiment results on a SIGIR publication collection show that the proposed methods are effective for generating impact-based sum- maries.