SEAL: Scientific Keyphrase Extraction and Classification
June 05, 2020 Β· Declared Dead Β· π 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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