论文标题
密封：科学键形提取和分类
SEAL: Scientific Keyphrase Extraction and Classification
论文作者
论文摘要
自动科学钥匙拼式提取是一个具有挑战性的问题，促进了几项下游学术任务，例如搜索，建议和排名。在本文中，我们引入了SEAL，这是一种用于自动键形提取和分类的学术工具。键形提取模块包括由双向长期记忆细胞组成的两阶段神经架构，并用条件随机场增强。分类模块包括一个随机的森林分类器。我们进行了广泛的试验以展示系统的鲁棒性。我们评估多个最先进的基线并显示出显着改善。当前系统托管在http://lingo.iitgn.ac.in:5000/上。
Automatic scientific keyphrase extraction is a challenging problem facilitating several downstream scholarly tasks like search, recommendation, and ranking. In this paper, we introduce SEAL, a scholarly tool for automatic keyphrase extraction and classification. The keyphrase extraction module comprises two-stage neural architecture composed of Bidirectional Long Short-Term Memory cells augmented with Conditional Random Fields. The classification module comprises of a Random Forest classifier. We extensively experiment to showcase the robustness of the system. We evaluate multiple state-of-the-art baselines and show a significant improvement. The current system is hosted at http://lingo.iitgn.ac.in:5000/.
