2018 NAACL NAACL 2018

Effective Crowdsourcing for a New Type of Summarization Task

Abstract

AbstractMost summarization research focuses on summarizing the entire given text, but in practice readers are often interested in only one aspect of the document or conversation. We propose targeted summarization as an umbrella category for summarization tasks that intentionally consider only parts of the input data. This covers query-based summarization, update summarization, and a new task we propose where the goal is to summarize a particular aspect of a document. However, collecting data for this new task is hard because directly asking annotators (e.g., crowd workers) to write summaries leads to data with low accuracy when there are a large number of facts to include. We introduce a novel crowdsourcing workflow, Pin-Refine, that allows us to collect high-quality summaries for our task, a necessary step for the development of automatic systems.

📈 Trend Setter — Summarization
🧭 Keyword Pioneer — human computation
🐝 Cross-Pollinator — Artificial Intelligence, Data Science & Analytics, Deep Learning, Machine Learning, Natural Language Processing, Speech & Audio
🌉 Interdisciplinary Bridge — Machine Learning and Natural Language Processing
🐣 Hot Topic Early Bird — data annotation