News events such as protests, accidents or natural disasters represent a unique information access problem where traditional approaches fail. For example, immediately after an event, the corpus may be sparsely populated with relevant content. Even when, after a few hours, relevant content becomes available, it is often inaccurate or highly redundant. At the same time, crisis events demonstrate a scenario where users urgently need information, especially if they are directly affected by the event. The goal of this track is to develop systems for efficiently monitoring the information associated with an event over time. Specifically, we are interested in developing systems which can broadcast short, relevant, and reliable sentencelength updates about a developing event.
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@inproceedings{trects2014:overview,
year = {2014},
title = {{TREC} 2014 Temporal Summarization Track Overview},
publisher = {NIST},
note = {Special Publication},
booktitle = {The 23rd Text Retrieval Conference Proceedings (TREC 2014)},
author = {Javed Aslam and Matthew Ekstrand-Abueg and Virgi Pavlu and Fernando Diaz and Richard McCreadie and Tetsuya Sakai}
}