论文标题
Deeplens：实体摘要的深度学习
DeepLENS: Deep Learning for Entity Summarization
论文作者
论文摘要
实体摘要是知识图的重要任务。尽管现有方法主要是无监督的，但我们提出了一个简单而有效的深度学习模型，我们利用文本语义来编码三元组，并且我们根据其相互依存的其他三元组来得分三倍。 Deeplens在公共基准上大大优于现有方法。
Entity summarization has been a prominent task over knowledge graphs. While existing methods are mainly unsupervised, we present DeepLENS, a simple yet effective deep learning model where we exploit textual semantics for encoding triples and we score each candidate triple based on its interdependence on other triples. DeepLENS significantly outperformed existing methods on a public benchmark.
