  We present a new summarization task, generating summaries of novel chapters
using summary/chapter pairs from online study guides. This is a harder task
than the news summarization task, given the chapter length as well as the
extreme paraphrasing and generalization found in the summaries. We focus on
extractive summarization, which requires the creation of a gold-standard set of
extractive summaries. We present a new metric for aligning reference summary
sentences with chapter sentences to create gold extracts and also experiment
with different alignment methods. Our experiments demonstrate significant
improvement over prior alignment approaches for our task as shown through
automatic metrics and a crowd-sourced pyramid analysis. We make our data
collection scripts available at
https://github.com/manestay/novel-chapter-dataset .
