Real-Time Web Scale Event Summarization Using Sequential Decision Making
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.
@inproceedings{ijcai2016p528,
title = {Real-Time Web Scale Event Summarization Using Sequential Decision Making},
author = {Kedzie, Chris and Diaz, Fernando and McKeown, Kathleen R.},
booktitle = {Proceedings of the Twenty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-16}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Subbarao Kambhampati},
pages = {3754--3759},
year = {2016},
month = {7},
url = {https://ijcai.org/proceedings/2016/528},
}
TY - CPAPER TI - Real-Time Web Scale Event Summarization Using Sequential Decision Making AU - Kedzie, Chris AU - Diaz, Fernando AU - McKeown, Kathleen R. T2 - Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2016 SP - 3754 EP - 3759 UR - https://ijcai.org/proceedings/2016/528 ER -Copied
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