Proceedings

Real-Time Web Scale Event Summarization Using Sequential Decision Making

Download BibTeX Cite

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Pages 3754-3759.

Abstract

We present a system based on sequential decision making for the online summarization of massive document streams, such as those found on the web. Given an event of interest (e.g. Boston Marathon bombing), our system is able to filter the stream for relevance and produce a series of short text updates describing the event as it unfolds over time. Unlike previous work, our approach is able to jointly model the relevance, comprehensiveness, novelty, and timeliness required by time-sensitive queries. We demonstrate a 28.3% improvement in summary F1 and a 43.8% improvement in time-sensitive F1 metrics.

Chris Kedzie, Fernando Diaz, and Kathleen R. McKeown. 2016. Real-Time Web Scale Event Summarization Using Sequential Decision Making. In Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16. IJCAI, 3754–3759. https://ijcai.org/proceedings/2016/528
Welcome Future Conferences AI Journal Division IJCAI Proceedings About IJCAI IJCAI Awards