SEAL: Scientific Keyphrase Extraction and Classification

June 05, 2020 Β· Declared Dead Β· πŸ› ACM/IEEE Joint Conference on Digital Libraries

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Authors Ayush Garg, Sammed Shantinath Kagi, Mayank Singh arXiv ID 2006.03292 Category cs.IR: Information Retrieval Cross-listed cs.CL Citations 1 Venue ACM/IEEE Joint Conference on Digital Libraries Last Checked 4 months ago
Abstract
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/.
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