Research Area:  Machine Learning
To achieve state-of-the-art performance, keyphrase extraction systems rely on domain-specific knowledge and sophisticated features. In this paper, we propose a neural network architecture based on a Bidirectional Long Short-Term Memory Recurrent Neural Network that is able to detect the main topics on the input documents without the need of defining new hand-crafted features. A preliminary experimental evaluation on the well-known INSPEC dataset confirms the effectiveness of the proposed solution.
Keywords:  
Lstm
Recurrent Neural Network
Keyphrase Extraction
neural network architecture
Machine Learning
Deep Learning
Author(s) Name:  Marco Basaldella, Elisa Antolli, Giuseppe Serra & Carlo Tasso
Journal name:  
Conferrence name:  Digital Libraries and Multimedia Archives
Publisher name:  Springer
DOI:   10.1007/978-3-319-73165-0_18
Volume Information:  
Paper Link:   https://link.springer.com/chapter/10.1007/978-3-319-73165-0_18