论文标题
在新闻时间表汇总中检查最新的
Examining the State-of-the-Art in News Timeline Summarization
论文作者
论文摘要
关于自动新闻时间轴摘要（TLS）的先前工作留下了一个不清楚的情况，说明通常如何处理此任务以及目前如何解决该任务。这主要是由于关注单个子任务的重点，例如日期选择和日期摘要，以及以前缺乏完整TLS任务的适当评估指标。在本文中，我们使用适当的评估框架比较了不同的TLS策略，并提出了一种简单有效的方法组合，这些方法可以改善所有测试基准的最先进的方法。为了进行更强大的评估，我们还提供了一个新的TLS数据集，该数据集比以前的数据集更大且跨度更长。
Previous work on automatic news timeline summarization (TLS) leaves an unclear picture about how this task can generally be approached and how well it is currently solved. This is mostly due to the focus on individual subtasks, such as date selection and date summarization, and to the previous lack of appropriate evaluation metrics for the full TLS task. In this paper, we compare different TLS strategies using appropriate evaluation frameworks, and propose a simple and effective combination of methods that improves over the state-of-the-art on all tested benchmarks. For a more robust evaluation, we also present a new TLS dataset, which is larger and spans longer time periods than previous datasets.
